Dengue Bulletin.indb - World Health Organization

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ISSN 0250-8362
The WHO Regional Office for South-East Asia, in collaboration with the Western
Pacific Region, has been jointly publishing the annual Dengue Bulletin.
Dengue Bulletin
The objective of the Bulletin is to disseminate updated information on the current
status of DF/DHF infection, changing epidemiological patterns, new attempted
control strategies, clinical management, information about circulating DENV strains
and all other related aspects. The Bulletin also accepts review articles, short notes,
book reviews and letters to the editor on DF/DHF-related subjects. Proceedings of
national/international meetings for information of research workers and programme
managers are also published.
All manuscripts received for publication are subjected to in-house review by
professional experts and are peer-reviewed by international experts in the
respective disciplines.
Volume 35, December 2011
South-East Asia Region
Western Pacific Region
Dengue
Bulletin
I S S N 0250- 8362
From the Editor’s Desk
D
engue fever/dengue haemorrhagic fever continued its accelerated pace in the countries of
the South-East Asia and the Western Pacific regions of the World Health Organization
(WHO).
During 2010, Member countries in the South-East Asia Region reported 293 868 cases with
1896 deaths (case-fatality rate (CFR) 0.65%). These are the highest figures reported over the last
five years. Bhutan and Nepal started regular reporting of dengue cases in 2006, and, during 2010,
reported 16 and 917 cases, with a disease incidence of 2.29 and 3.18 per 100 000 population,
respectively. India, Indonesia, Maldives, Myanmar, Sri Lanka and Thailand reported more than 10
000 cases each, with a disease incidence of 2.29, 66.03, 307.54, 30.56, 164.76 and 85.09 per
100 000 population, respectively.
Member countries in the Western Pacific Region, reported 354 000 cases with 1075 deaths
(CFR 0.30%) in 2010. The countries that reported a significant number of cases are: Australia,
Cambodia, Malaysia, Philippines, Singapore and Viet Nam. However, only Cambodia and
Singapore reported more cases than those reported a year before.
To arrest this rising trend of dengue, development of a vaccine is the only answer. As several
promising live-attenuated vaccine candidates are currently in the later stages of clinical
development, WHO in collaboration with many international researchers/institutions, has
developed guidelines which are focused on the design of pivotal efficacy trails that can inform
national regulatory authorities and vaccine developers.
During 2010, Crimean-Congo Haemorrhagic Fever (CCHF), a disease related to arboviral
haemorrhagic fevers, caused by Nairovirus, family Bunyaviridae, transmitted by ticks, surfaced in
the Indian subcontinent. A total of 10 cases with four deaths were reported from Gujarat state,
India. Twenty-six cases with three deaths were also reported from Pakistan.
The current volume of Dengue Bulletin (No. 35, 2011) contains contributions from authors
in the WHO regions of South-East Asia (14), the Western Pacific (5), the Eastern Mediterrean (3),
the Americas (1) and Europe (1).
We now invite contributions for Volume 36 (2012). The deadline for the receipt of
contributions is 31 June 2012. Contributors are requested to please peruse the instructions given
at the end of the Bulletin while preparing their manuscripts. Contributions should either be sent
accompanied by CD-ROMs to the Editor, Dengue Bulletin, WHO Regional Office for South-East
Asia, Mahatma Gandhi Road, I.P. Estate, Ring Road, New Delhi 110002, India, or by e-mail as a
file attachment to the Editor at [email protected]. Readers desirous of obtaining copies of
the Dengue Bulletin may write to the WHO Regional Offices in New Delhi or Manila or the WHO
Country Representative in their country of residence.
Dr A.P. Dash
Regional Adviser, Vector-Borne and Neglected
Tropical Diseases Control (RA-VBN), and
Editor, Dengue Bulletin
World Health Organization
Regional Office for South-East Asia
New Delhi, India
Dengue
Bulletin
ISSN 0250-8362
© World Health Organization 2011
Publications of the World Health Organization enjoy copyright protection in accordance
with the provisions of Protocol 2 of the Universal Copyright Convention. For rights of
reproduction or translation, in part or in toto, of publications issued by the WHO
Regional Office for South-East Asia, application should be made to the Regional Office
for South-East Asia, World Health House, Indraprastha Estate, New Delhi 110002, India.
The designations employed and the presentation of the material in this publication
do not imply the expression of any opinion whatsoever on the part of the Secretariat of
the World Health Organization concerning the legal status of any country, territory, city
or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.
The views expressed in this publication are those of the authors and do not
necessarily reflect the decisions or stated policy of the World Health Organization;
however they focus on issues that have been recognized by the Organization and
Member States as being of high priority.
Printed in India
Indexation: Dengue Bulletin is being indexed by BIOSIS and
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Acknowledgements
The Editor, Dengue Bulletin, WHO/SEARO, gratefully thanks the following for peer reviewing
manuscripts submitted for publication.
1.
Anon Srikiatkhachorn
Department of Medicine
University of Massachusetts Medical School
Worcester, Massachusetts 01655, USA.
E-mail: [email protected]
8.
Dave Chadee
Department of Life Sciences
The University of the West Indies
St. Augustine, Trinidad and Tobago
2.
Anuja Mathew
S6-868, Infectious Disease and Immunology
University of Massachusetts Medical School
55 Lake Avenue North
Worcester, MA 01655, USA
9.
Denise Valle
Oswaldo Cruz Institute
Oswaldo Cruz Foundation
Rio de Janeiro, Brazil
3.
4.
5.
Audrey Lenhart
Liverpool School of Tropical Medicine
Vector Group, Pembroke Place
Liverpool, L3 5QA, UK
Brian Kay
Australian Centre for International and
Tropical Health
Queensland Institute of Medical Research
Brisbane, Queensland, Australia
Chang Moh Seng
Regional Office for the Western Pacific
(WPRO), P.O. Box 2932
1000 Manila, Philippines
6.
Christophe Paupy
Centre International de Recherches
Médicales de Franceville (CIRMF)
BP 769 Franceville, Gabon
7.
Clara J. Witt
Armed Forces Health Surveillance Center
503 Robert Grant Avenue
Silver Spring, MD 20910, USA
Dengue Bulletin – Volume 35, 2011
10. Dinesh Srivastava
Ram Manohar Lohia Hospital
New Delhi
11. Duane Gubler
Signature Research Program - Emerging
Infectious Diseases
Duke-NUS Graduate Medical School
8 College Road, Singapore 169857
12. Eng Eong Ooi
Duke-NUS Graduate Medical School
8 College Road, Singapore 169857
13. Goro Kuno
1648 Collindale Drive, Fort Collins
CO 80525, USA
14. Grégory L’Ambert
Direction Technique
EID Méditerranée
165, Avenue Paul-Rimbaud
F-34184 Montpellier Cedex 4, France
iii
15. Guey Chuen Perng
Department of Pathology and Laboratory
Medicine
Emory Vaccine Center
Emory University School of Medicine
Atlanta, Ga., USA
16. Hoang Lan Phuong
Dept. of Tropical Diseases
Choray Hospital
201B Nguyen Chi Thanh St, District 5
Ho Chi Minh city, Vietnam
17. Jennifer Kyle
Division of Infectious Diseases and
Vaccinology
School of Public Health
University of California, Berkeley
Berkeley, California, USA
18. Lars Eisen
Colorado State University
Department of Microbiology, Immunology
and Pathology
1690 Campus Delivery
Fort Collins, CO 80523, USA
19. Laurence Després
Laboratoire d’Ecologie Alpine
UMR CNRS 5553, Université Joseph Fourier
BP 53, 38041, Grenoble Cedex 09, France
20. Lian Huat Tan
Department of Internal Medicine
Faculty of Medicine
University of Malaya, Malaysia
21. Linda Kaljee
Pediatric Prevention Research Center
The Carman and Ann Adams Department
of Pediatrics
Wayne State University
Hutzel Building,
Suite W534, 4707 St. Antoine
Detroit, MI, 48201, USA
iv
22. Linda Lloyd
443 Whittier St.
San Diego, CA 92106, USA
23. Lucy Lum Chai See
Department of Paediatrics
Faculty of Medicine
University of Malaya
Kuala Lumpur, Malaysia
24. Mark Q Benedict
Centers for Disease Control and Prevention
Atlanta, Georgia 30341, USA
25. Martin Peter Grobusch
Center for Tropical Medicine and
Travel Medicine
Department of Infectious Diseases
Division of Internal Medicine
Academic Medical Center
University of Amsterdam
Meibergdreef 9, PO Box 22660
1100 DD Amsterdam, The Netherlands
26. Morteza Zaim
WHO Pesticide Evaluation Scheme
(WHOPES)
Vector Ecology & Management
Department of Control of Neglected
Tropical Diseases
20 Avenue Appia
CH-1211 Geneva 27, Switzerland
27. Nguyen Thanh Hung
Department of Dengue Hemorrhagic Fever
Children’s Hospital No. 1
Ho Chi Minh City, Vietnam
28. Paris Margot
Institute of Integrative Biology
Plant Ecological Genetics
Universitätsstrasse 16 CHN G 31.1
CH-8092 Zürich, Switzerland
29. Philippe Buchy
Virology Unit
Institut Pasteur in Cambodia
Phnom Penh, Cambodia
36. Scott B. Halstead
Pediatric Dengue Vaccine Initiative
Kwanak PO Box 14
Seoul, Korea 151-600
30. Raman Velayudhan
Vector Ecology and Management
Department of Control of Neglected
Tropical Diseases (HTM/NTD)
20 Avenue Appia
CH-1211 Geneva 27, SWITZERLAND
37. Siripen Kalayanarooj
WHO Collaborating Centre for Case
Management of Dengue/DHF/DSS
Queen Sirikit National Institute of
Child Health
Department of Medical Services
Ministry of Public Health
Bangkok, Thailand
31. Rivaldo Venâncio da Cunha
Fiocruz Cerrado Pantanal/Universidade
Federal de Mato Grosso do Sul
Campo Grande, Brasil.
32. S.R. Loke
Institute of Biological Sciences
Faculty of Science
Universiti Malaya
50603 Kuala Lumpur, Malaysia
33. Sander Koenraadt
Laboratory of Entomology
Wageningen University
Building 107/Radix, W0.Aa.081 Desk 17
Droevendaalsesteeg 1
6708 PB Wageningen, The Netherlands
34. Sandra Jackson
National Influenza Centre-Jamaica
Department of Microbiology
Virology Laboratory
University of the West Indies
Mona Campus
Kingston 7, Jamaica
35. Elizabeth Hunsperger
Serology and Viral Pathogenesis Research
Laboratory
Dengue Branch
Division of Vector Borne Infectious Diseases
1324 Calle Canada, San Juan, PR 00920
38. Trevor Williams
Instituto de Ecologia AC
Xalapa, Veracruz 91070, Mexico
39. Veerle Vanlerberghe
Unit of Epidemiology and Disease Control
Public Health Department
Institute of Tropical Medicine
Nationalestraat 155
Antwerp, Belgium
40. Vijay K. Saxena
Independent Consultant
(Vector Borne Diseases)
41. Vu Sinh Nam
General Department of Preventive Medicine
Ministry of Health of Vietnam
Alley 135 Nui Truc, Ba Dinh
Hanoi, Vietnam
42. William A. Hawley
Atlanta, Georgia 30341, USA
v
The quality and scientific stature of the Dengue Bulletin is largely due to the conscientious
efforts of the experts and also due to the positive response of contributors to comments and
suggestions.
In-house review: The manuscripts have also been reviewed in house by Mr Nand Lal Kalra
in respect of format, content, conclusions drawn, including condensation of tabular and
illustrative materials for clear, concise and focused presentation and bibliographic references.
He was also involved in the final stages of printing of the Bulletin.
WHO/SEARO – The Editor thanks Ms Anchalee Chamchuklin, Librarian, Information
Management & Dissemination, and her staff for crosschecking the accuracy and arranging the
references as per the Vancouver style. The Editor is also thankful to Dr Rakesh Mani Rastogi,
Technical Officer (Surveillance Monitoring and Evaluation) for his support in reviewing the
GIS related papers.
vi
Contents
1.
Overcoming data limitations: design of a multi-component study for
estimating the economic burden of dengue in India.......................................... 1
Yara A. Halasa, Vishal Dogra, Narendra Arora, B.K. Tyagi, Deoki Nandan & Donald S. Shepard
2.
Identifying and visualizing spatial patterns and hot spots of
clinically-confirmed dengue fever cases and female Aedes aegypti
mosquitoes in Jeddah, Saudi Arabia ................................................................ 15
Hassan Muhsan Khormi & Lalit Kumar
3.
Update on dengue in Africa............................................................................ 35
Fernando R.R. Teles
4.
Involvement of the central nervous system in dengue fever and its outcome ... 52
M.L. Kulkarni & Saurabh Kumar
5.
Clinical and biochemical characteristics of suspected dengue fever
in an ambulatory care family medical clinic, Aga Khan University,
Karachi, Pakistan ............................................................................................ 59
Firdous Jahan, Kashmira Nanji, Waris Qidwai, Rozina Roshan & Hira Waseem
6.
Capillary leak syndrome in dengue fever ........................................................ 65
Sudhir Kumar Verma, Manish Gutch, Abhishek Agarwal & A.K. Vaish
7.
Haemogram profile of dengue fever in adults during
19 September – 12 November 2008: A study of 40 cases from Delhi ............. 71
Sonia Advani, Shikha Agarwal & Jitender Verma
8.
Differentiating early adult dengue from acute viral respiratory
infections – A comparative analysis ................................................................. 76
Tun-Linn Thein, Eng-Eong Ooi, Jenny GH Low & Yee-Sin Leo
9.
Evaluation of an immunochromatographic test for early and rapid
detection of dengue virus infection in the context of Bangladesh .................... 84
Rabeya Sharmin, Shahina Tabassum, Munira Jahan, Afzalun Nessa & K.Z. Mamun
10. A hypothetical intervention to reduce plasma leakage in
dengue haemorrhagic fever ........................................................................... 94
Kolitha H. Sellahewa
vii
11. Entomological investigations of dengue vectors in epidemic-prone
districts of Pakistan during 2006–2010 ............................................................ 99
Muhammad Mukhtar, Zarfishan Tahir, Taj Muhammad Baloch, Faisal Mansoor & Jaleel Kamran
12. Geographical association between socioeconomics and age of dengue
haemorrhagic fever patients in Surabaya, Indonesia ...................................... 116
Yoshiro Nagao, Esty M. Rachmie, Shiro Ochi, Maria M. Padmidewi, Kuntarianto
& Masato Kawabata
13. Aedes aegypti indices and KAP study in Sangam Vihar, south Delhi,
during the XIX Commonwealth Games, New Delhi, 2010 ............................ 131
R.K. Singh, P.K. Mittal, N.K. Yadav, O.P. Gehlot & R.C. Dhiman
14. Pupal/demographic and adult aspiration surveys of residential and
public sites in Yogyakarta, Indonesia, to inform development of a
targeted source control strategy for dengue .................................................. 141
Sugeng J. Mardihusodo, Tri Baskoro T. Satoto, A. Garcia & Dana A. Focks
15. Ovitrap surveillance of dengue and chikungunya vectors in several
suburban residential areas in Peninsular Malaysia.......................................... 153
Lim Kwee Wee, Norzahira Raduan, Sing Kong Wah, Wong Hong Ming, Chew Hwai Shi,
Firdaus Rambli, Cheryl Jacyln Ahok, Nazni Wasi Ahmad, Lee Han Lim, Andrew McKemey &
Seshadri Vasanb
16. Specifying skills for proficient control of Aedes aegypti oviposition
in flowerpot saucers through the use of net covers ........................................ 161
João Bosco Jardim, Ana Carolina Bocewicz & Virgínia Torres Schall
17. Evaluation of Mesocyclops aspericornis, Mesocyclops ogunnus and
Mesocyclops thermocyclopoides from the water bodies of Chennai
(south India) as control agents of Aedes aegypti ............................................. 173
Zehra Amtuz & Nasarin A.
18. Misting of Bacillus thuringiensis israelensis (Bti) to control
Aedes albopictus in an industrial area – the Singapore experience ............... 181
S. Dulangi M. Sumanadasa, Caleb Lee, Sai Gek Lam-Phua, Deng Lu, Lee-Pei Chiang,
Sin-Ying Koou, Cheong-Huat Tan, Sook-Cheng Pang, Nasir Maideen, Lee-Ching Ng
& Indra Vythilingam
19. Susceptibility of Aedes aegypti to insecticides in Ranchi city,
Jharkhand state, India ................................................................................... 194
M.K. Das, R.K. Singh, R.K. Lal & R.C. Dhiman
viii
20. Dengue awareness survey among women participants from periurban
areas of Chennai, India ................................................................................. 199
R. Ramanibai & Kanniga S.
21. Association between dengue virus serotypes and type of dengue
viral infection in Department of Child Health, Cipto Mangunkusumo
Hospital, Jakarta, Indonesia .......................................................................... 205
Dimas Seto Prasetyo, Angky Budianti, Beti Ernawati Dewi, Cucunawangsih,
Roni Chandra, Jordan Chaidir, Mulya Rahma Karyanti, Hindra Irawan Satari,
Aria Kekalih, Ichiro Kurane & T. Mirawati Sudiro
Short Notes
22. Study of prevalent practices about use of platelets in management of
dengue cases in selected tertiary care hospitals in Delhi in 2009 .................. 214
K.N. Tewari, N.R. Tuli & S.C. Devgan
23. Demographic features of imported dengue fever and dengue
haemorrhagic fever in Japan from 2006 to 2009 ...............................................217
Tomohiko Takasaki, Akira Kotaki, Shigeru Tajima, Tsutomu Omatsu, Fumiue Harada,
Chang-Kweng Lim, Meng Ling Moi, Mikako Ito, Makiko Ikeda & Ichiro Kurane
24. Evaluating school students’ perception about mosquitoes and
mosquito-borne diseases in the city of Kolkata, India .................................... 223
D. Biswas, Baishakhi Biswas, Bithika Mandal, A. Banerjee, T.K. Mukherjee & J. Nandi
Book reviews
25. Comprehensive guidelines for prevention and control of dengue and
dengue haemorrhagic fever .......................................................................... 231
26. Progress and prospects for the use of genetically modified mosquitoes
to inhibit disease transmission....................................................................... 234
27. Action against dengue: Dengue Day campaigns across Asia .......................... 236
28. Crimean-Congo haemorrhagic fever (CCHF) and dengue fever, Pakistan ....... 237
29. Instructions for contributors .......................................................................... 238
ix
Overcoming data limitations: design of a multicomponent study for estimating the economic burden
of dengue in India
Yara A. Halasa,a Vishal Dogra,b Narendra Arora,b B.K. Tyagi,c Deoki Nandand &
Donald S. Sheparda#
Schneider Institutes for Health Policy, Heller School, Brandeis University,
Waltham, MA 02454-9110, USA.
a
International Clinical Epidemiology Network (INCLEN), New Delhi, India.
b
Centre for Research in Medical Entomology (Indian Council of Medical Research),
4, Sarojini Street, China Chokikulam, Madurai-625 002, Tamil Nadu, India.
c
d
National Institute for Health and Family Welfare, Baba Gang Nath Marg,
Munirka, New Delhi-110067, India.
Abstract
Dengue is emerging as a serious global health problem. Estimating the economic burden of dengue
is crucial to inform policy-makers of the disease’s societal impact and may assist in implementing
appropriate control strategies. However, developing such studies is constrained by limited data and
other challenges. This paper shows how analyzing hospital records carefully can adjust surveillance
data for possible under-reporting and misdiagnosis of dengue, merging information on treatment
patterns with macro costing to estimate the cost of dengue episode by age and severity in various
treatment settings, and combining adjusted surveillance data with cost information can estimate
the aggregate cost of dengue illness in India and in other endemic countries.
Keywords: Dengue; Burden; Cost; Surveillance; Expansion, India.
Introduction
Dengue is emerging as a serious public health problem globally, with 2.5 billion people
at risk and 50 million dengue infections occurring annually.[1-4] Estimates of the economic
burden of dengue are important in order to inform policies on dengue prevention and
management, but published studies on this subject are limited.[5,6] This paper presents an
#
1
Estimating the economic burden of dengue in India
approach to estimate the economic burden of dengue illness in India. It utilizes several tools
to assess the coverage of the dengue surveillance system: estimating an expansion factor to
correct under-reporting and under-diagnosis, computing the average cost of a dengue illness
episode, and aggregating direct and indirect costs.
Dengue is caused by four closely-related but serologically-distinct dengue viruses:
DENV-1, DENV-2, DENV-3 and DENV-4. Lifetime immunity to each serotype follows an
infection by that serotype. However, individuals infected with one or more serotypes remain
vulnerable to infections by the other dengue serotypes.[7,8] Dengue infections affect all age
groups and produce a spectrum of clinical manifestations, with varied clinical evolutions
and outcomes that range from asymptomatic to a mild or non-specific viral syndrome and
to a severe and occasionally fatal disease characterized by haemorrhage and shock.[3,9-11]
Primary infection (the first dengue infection caused by any of the four serotypes) is often
asymptomatic, but primary infections sometimes result in dengue fever, a very uncomfortable
febrile illness. However, secondary dengue infections can lead to the life-threatening dengue
haemorrhagic fever (DHF) or dengue shock syndrome (DSS).[12-16] Epidemiological studies
have demonstrated that secondary or subsequent dengue infections contribute to higher
rates of DHF in Thailand and Cuba.[17-22] Several hypotheses may explain the pathogenesis
of severe dengue.[23-25]
Dengue challenge in India
Dengue is becoming a serious public health problem in India.[26-29] Although dengue infection
has been endemic in India since the nineteenth century, DHF has become endemic in
various parts of India since 1987, with the first major widespread epidemics of DHF and DSS
occurring in 1996, involving areas around Delhi and Lucknow, Uttar Pradesh, and spreading
to other regions in India.[30-33] However, the epidemics of Delhi and Pune in western India in
2006 and in Kerala state in 2008 marked the changing epidemiology of dengue infection,
with all four serotypes of dengue viruses found in co-circulation, leading to an increase in
secondary dengue infection and, in some cases, co-infections with DENV-1 and DENV-3,
DENV-2 and DENV-3 and DENV-1, DENV-2 and DENV-3.[11-13,26,27,31,34,35] In West Bengal
state, nearly 61% of dengue cases reported between 2005 and 2007 were secondary dengue
infection cases.[36] Moreover, some studies revealed the evolving phylogeny (change through
time) of DENV-3 and DENV-4 and their circulation in South-East Asia and India, emphasizing
higher risks of DHF/DSS outbreaks.[13,37]
With these epidemiological developments, dengue infection changed its manifestation
in India from the infection’s asymptomatic and benign form to its severe forms of DHF
and DSS, with increasing frequency of outbreak, morbidity and mortality.[10,11,27,30-33,36,38-45]
Although dengue is considered an urban and semi-urban disease, in recent years, due to
water storage practices and large-scale development activities in rural areas, dengue has
become endemic in rural areas of India as well, increasing the scale of the dengue challenge
in the country.[36,45-48]
2
After the 1996 dengue haemorrhagic fever epidemic in Delhi, dengue was declared a
dangerous disease under sections 2(9) (b) of the Delhi Municipal Corporation (DMC) Act,
1957 (Delhi Gazette Notification dated April 25 1997). Under this Act, all private practitioners,
nursing homes and government hospitals are required to notify suspected dengue cases to
the Municipal Health Officer.[29] However, under-diagnosis and under-reporting of dengue
cases persist in India, where reported cases underestimate the real burden of the disease.[49-51]
Similar to studies in Nicaragua and Thailand, a strict application of WHO criteria resulted in
the omission of many cases of DHF in India.[11] The WHO 1997 classification makes use of
symptoms and signs that are often not present in the first few days of illness and thus are not a
sufficient guide for early diagnosis without expensive laboratory investigations such as RT-PCR
or NS1; lack of these tools is likely to lead to under-diagnosis and under-reporting of severe
manifestations of dengue.[39,52] For example, during the 2010 dengue outbreak in Delhi, the
number of dengue cases was likely under-reported as platelet counts were not performed
immediately, nor were they followed by serological screening.[49,53] Additionally, medical
and public health professionals had less familiarity with investigating and managing dengue
than their counterparts in other countries where the disease is more endemic.[53] Access to
routine public laboratory testing of dengue (based on IgM antibodies) is limited to patients
treated in large public hospitals. This diagnostic tool is applicable only to samples obtained
six or more days after the onset of fever, and may still yield false negative results.[4] While
tests based on viral replication in cell culture, molecular investigations, immunofluorescence
or immunohistochemistry may be more accurate,[53-56] they are not generally feasible for
routine use.[23]
Several studies have addressed the burden of dengue illness in India. These studies were
facility-based, focused on tertiary care hospitals, and, in most cases, limited to one location
and a single outbreak study.[10,11,27,30-33,38-45,57] Moreover, only a handful of them examined the
economic cost of dengue in the country. While a useful start, these studies were limited by
examining only one sector (public or private), reliance on data from other countries (mainly
Thailand) for expansion factors, or a single geographical area.[58-62] With dengue’s changing
epidemiology, a broader study is needed to estimate the overall economic burden of the
disease in India. This paper sets forth a method designed to meet this need.
Proposed approach
Conceptual framework
In order to estimate the economic burden of dengue, ideally, data should be compiled from
multiple sources in the health system at different levels. At the national, regional and state
levels, surveillance data and expansion factors are needed to correct the under-reporting
and under-diagnosis of dengue cases. First, to address the variability of dengue, surveillance
data are needed for several years for all regions in India, preferably broken down by the
setting from which the case is reported, dengue classification or severity, and the patient’s
3
age. Second, an expansion factor is needed to adjust surveillance data to under-reporting
and provide reasonable estimates of dengue cases according to setting, severity and age. At
the facility and household levels, data are needed to estimate the overall economic cost of
a dengue episode according to treatment setting (hospitalized vs ambulatory) by a patient’s
age and case severity. The economic cost includes direct medical cost, direct non-medical
cost (i.e. transportation, meals and lodging), and indirect costs associated with the illness
episode (value of work, school or leisure time lost due to illness or care-giving). To estimate
the economic cost of dengue we compute the weighted average cost of dengue according to
care setting and patient’s age group. The figure below presents the proposed methodology
to overcome data limitations and respect time constraints. These steps are simple in concept
but challenging in practice due to lack of systematically compiled data.
Figure: Conceptual framework of the economic burden of dengue in India study
National and state level
Delphi panel for
expansion factor
Surveillance
data
Dengue
cases
Facility level
Macrocosting
Retrospective and
prospective
surveys of patients
Cost of a
dengue
episode
Aggregate economic cost of dengue
Study setting
This study represents a collaboration among academic and government institutions in India
and overseas. The participating institutions are: Brandeis University (Waltham, Massachusetts,
USA), the National Institute of Health and Family Welfare (New Delhi, India), the Centre
for Research in Medical Entomology of the Indian Council of Medical Research (Madurai,
India), and the International Clinical Epidemiology Network (INCLEN) (New Delhi, India).
This collaboration combines local knowledge and experience in vector transmission, virology
4
and epidemiology with the international expertise in costing the economic burden of
dengue. The study protocol was reviewed and approved by the Institutional Review Board
at Brandeis University, INCLEN Independent Ethics Committee and the Indian Council of
Medical Research, and was approved by participating institutions’ ethics boards prior to
collection of patient-level data.
Facility and household data: estimating the average cost of a
hospitalized dengue episode
For this study, India will be divided into five regions (south, north, west, east and central)
to capture the diversity among different regions in the country. Two states will be selected
from each region. One selected state in each region will represent a state in that region
with a relatively high incidence rate of reported dengue cases and the second selected state
will represent a state in that region with a relatively low incidence rate of reported dengue
cases. The incidence rates will be obtained from national, regional or state surveillance
systems and the official statistics of the Ministry of Health and Family Welfare starting with
the year 1996, when dengue reporting became mandatory. From each of these ten selected
states, one medical college hospital will be selected based on the availability of electronic
medical data, willingness to participate, and ability to meet the study timeline and the quality
requirement for this research.
A mixed approach will be used to obtain the economic cost of dengue, combining
retrospective and prospective data collection. The retrospective abstraction of data from
inpatient medical records and a prospective survey of ambulatory patients suspected of
having dengue, combined with a macro-costing analysis will be used to obtain the cost of
dengue according to treatment setting, age and severity for the year 2010. The reference
years for the retrospective component will be the last five years with available data, years
2006 through 2010, to cover a cyclical pattern in the number of cases across years, as well as
seasonal variation.[5,31] Study participants will be drawn from three populations: (1) patients
with a clinical discharge diagnosis of dengue (ICD10 code A90); (2) patients with discharge
diagnosis of any of the following febrile illnesses: chikungunya (A92.0), Khysanur forest disease
(A98.2), influenza-like illnesses or influenza and pneumonia (J09-J18), malaria (B52), typhoid
(Z22) and fever with rash and haemorrhage (A98.4-A99), who were hospitalized during the
dengue season starting 1 July through 30 November during the specified study years; and (3)
patients with a discharge diagnosis of fever or pyrexia of unknown origin (R50.9) hospitalized
during the dengue seasons mentioned above. A systematic random sample of 7500 medical
records is planned. The sample will consist of 150 hospitalized cases in each of 10 medical
colleges for each of five years. Each year’s sample consists of three strata reflecting the three
categories of the study population, each with 50 patients. If there are 50 patients or fewer
we will enroll all these patients in the study. If there are more than 50 patients, a systematic
random sample will be selected from that category after recording the sample frame. Based
5
on a previous multi-country study, we project that this sample will give accuracy in cost per
case of 9.3% for hospitalized cases. This level of precision will be adequate for measuring
trends or comparing regions.[63]
Using the definition of dengue febrile illnesses adopted by publications of the World
Health Organization in 1999 and 2011 (referring to the detection of dengue virus in patients
with two days of fever irrespective of severity of illness),[3,9,64-66] an evidence-based triage
strategy will be used to develop a prediction model to identify individuals likely to have
dengue infection, but have been misdiagnosed for another febrile disease. A data abstractor,
a professional with a medical or paramedical background, will review signs, symptoms,
notes and lab tests to see whether they are consistent with a diagnosis of dengue as stated
by the WHO-recommended surveillance standards 1999 classification of DF, DHF and DSS.
[66]
Based on the type of information available, such cases will be classified as confirmed
dengue, suspected dengue, indeterminate or non-dengue. Based on probability theory with
a dichotomous outcome, the sample size for each illness category should be proportional to
the variance in the expected number of cases in that category, n[p(1-p)]1/2, where ‘n’ is the
number of admissions in that category, and ‘p’ is the estimated probability that an admission
in that category is ‘suspected’ or ‘confirmed’ dengue. Data will be extracted from medical
records, with a careful review of laboratory and clinical records used to classify which cases
should be considered dengue. These data will be compiled to assess the probability of a
dengue case being misdiagnosed. These data will also be used to estimate the expansion
factor for institutions with good dengue reporting systems and an expansion factor for
institutions with weaker dengue reporting systems. The average of these two factors should
be a reasonable proxy for the national expansion factor for India.
The results will be tabulated to calculate arithmetic and weighted means, standard
deviations and standard error of the mean, t-tests, ANOVA and Chi-square tests with alpha
level of significance at 0.05. Sensitivity analyses will test the variation in the economic costs
among years and regions in India.
Facility and household data: estimating the average cost of an
ambulatory dengue episode
The prospective outpatient study will focus on dengue cases that received ambulatory
care only and will be implemented during the dengue season (July through November).
This component will be carried out in ambulatory facilities affiliated with one or two of
the participating medical college hospitals (those in Mumbai and Delhi are recommended,
for they have the most sophisticated laboratory capabilities and the highest proportions of
routine ambulatory patients with fever tested for dengue). The sample frame will consist of
all patients with acute febrile illness and clinically diagnosed dengue cases seeking treatment
during the study period. A field-trial approach using commercial dengue NS1 antigen-capture
for early laboratory confirmation of acute dengue will be utilized to obtain a sample of 100
6
confirmed dengue cases and 150 patients with fever or pyrexia of unknown origin. The
sample size is based on the previous multi-country study of dengue burden and costs. This
level of precision will be adequate for measuring trends.
A lab technician will make the first contact with outpatients sent to the affiliated hospital
laboratory for a dengue panel of tests (NS1 or IgM, platelets, haematology, packed cell volume
and haematocrit) or to investigate fever or pyrexia of unknown origin, to screen and explain
the objectives of the study to them and invite them or their proxy to participate and sign
a consent form. A second contact will occur when patients seek the results of the test and
physician’s diagnosis. At this point, patients will be divided into two groups. The first group will
consist of patients with positive dengue diagnosis. The second group will consist of patients
who are negative for dengue and diagnosed with fever or pyrexia of unknown origin. This
group will be randomized based on their outpatient department medical record number,
where those with even numbers will be retained in the study. The rationale of including
these patients is based on the inconclusiveness of the NS1 test to rule out dengue after 3-5
days of infection with dengue virus. A model will be developed to compare the symptoms
of patients with dengue and patients with fever or pyrexia of unknown origin to determine
the likelihood of dengue infection in this category of patients.
Two weeks after the initial screening, where we hypothesize that the illness episode will
be over, all patients remaining in the study will be asked to complete a survey. A standardized
survey instrument will be used. It includes a section from the World Health Survey and
EuroQol (visual scale) to measure the quality of life. The survey will ascertain the clinical
characteristics of the patient’s illness such as days of fever, days of overall illness, perceived
severity and quality of life, and care-seeking behaviour, as well as an assessment of the
socioeconomic impact on the patient and his/her household. Cost-related domains include
the cost associated with the use of medical services, days of schooling lost, loss in work
productivity and income, leisure time lost due to illness or care-giving, and out-of-pocket
spending. To complement the clinical information obtained from the patients during the
interviews, medical records will be reviewed at the selected ambulatory facility to extract
relevant clinical data (e.g. days of fever, clinical manifestations such as vomiting, diarrhoea,
etc.) and laboratory data (e.g. platelet and white cell count, hematocrit, radiological results,
etc.) associated with that illness episode.
A full economic analysis from a societal perspective will be conducted by combining
the three major cost categories: direct medical, direct non-medical and indirect costs. To
compute the direct medical costs for each patient, we will sum the type and amount of services
received by ambulatory setting and by provider and multiply this by their respective unit
costs. We will use each patient’s actual out-of-pocket payments for costing private medical
services. To calculate direct non-medical costs we will aggregate the out-of-pocket payments
by the patients and their household and care-givers for transportation, food, lodging and
related miscellaneous expenses.
7
To estimate the indirect cost for the dengue episode, we will compute the monetary
values of the time lost due to days of school missed; days of work lost (paid and unpaid);
and leisure time lost due to illness or care-giving. The economic loss attributed to school
days lost will be calculated by multiplying the cost of a school-day in a public school by the
number of school days lost. The societal value of a day of work lost and leisure time lost
will be valued as the larger of the worker’s reported income lost per day or India’s daily
minimum wage. The total economic costs of work days lost will be calculated as the product
of this average daily loss and the number of work days lost. Finally, the total cost of a dengue
case will be calculated for each patient as the sum of all his or her direct (medical and nonmedical) and indirect costs.
The cost will focus only on one episode of illness and all the treatment and cost
associated with that episode. The results will be reported as means and standards deviations
for continuous variables and frequencies for categorical variables. T-test and Chi square test
with alpha level of significance at 0.05 will be performed for key analyses.
To estimate the economic cost of the medical care provided by medical college hospitals,
a macro-costing approach will be used. It entails three stages. First, using admissions, length
of stay and numbers of ambulatory visits in the selected facilities, we can estimate the
hospital’s annual number of hospital-day equivalents. This estimation will be computed by
multiplying the annual number of admissions by the average length of stay and the number
of hospital outpatient visits by 0.25, based on the observation that the cost of a hospital
outpatient visit was one fourth of a hospital day.[67] Second, to calculate the average cost
of a hospital day, we will divide the hospital’s total annual expenses by the total number
of hospital-day equivalents. Third, as we assume that the public ambulatory care will be
provided not only by selected ambulatory facilities but also by other health centres and
dispensaries, we expect that the cost of a public ambulatory visit would be 60% of the cost
of a hospital outpatient visit.[63]
National- and state-levels surveillance data and expansion factors
The dengue surveillance system in India consists of 330 facilities supported by 14 apex
laboratories across the country.[68,69] The system is designed to monitor outbreaks and guide
responses. The current surveillance system does not currently capture all dengue cases. To
address the under-reporting dilemma in India, a structured communication technique for
interactive forecasting known as the “Delphi method” will be used to estimate the expansion
factors for various settings, age groups and regions in India. Information from different sectors
will be gathered prior to this meeting to assist the process. Supplementary information, such
as the number of dengue test kits distributed by type and year for the two most widely used
types of initial test (Mac Elisa IgM and NS1), can assist in estimating the number of dengue
cases by state. Using an individual test as a unit of measure, this component will create two
inventories of supplies reflecting domestic and foreign wholesale suppliers, including both
public and private suppliers, to estimate the average number of units by year and type of
8
supplier. Using inventory and reported data we can compute the number of suppliers of
each type and their average volume by type. Multiplying these two estimates will give the
number of tests by year. Since few patients get both types of tests and these tests are generally
not repeated, the sum of the two types of data will be used to estimate the total number of
patients tested by year.
In order to determine the number of dengue patients treated by year in the formal health
system in the selected states, an inventory of health facilities by type for the year 2010 will
be generated. The average number of dengue patients per year by type of facility will be
estimated using a sample of at least two facilities of each type (inpatient and outpatient).
The Delphi process can be conducted in two or more stages. In the first stage, key experts
in various areas related to dengue from governmental, academic and private sectors will jointly
share their knowledge and experience in a one- or two-day workshop, and answer preset
questions related to the epidemiology of dengue and the quality of the surveillance system
in India when it comes to reporting mechanisms from all settings (hospital vs ambulatory;
public vs private; municipality vs state vs national surveillance system; rural vs urban). The
second stage will take place two weeks after the workshop. A report, with the suggested
estimates, will be sent to the experts and they will be asked to refine their own estimates,
if needed, according to the workshop discussions and the results generated from the first
round. The experts can collectively share their knowledge about dengue treatment patterns
in the public and private sectors and the process of recording dengue illness to estimate the
completeness of reporting in each setting.
National-, regional- as well as state-levels dengue surveillance data will be collected
and compared. A special instrument will be developed to collect data at the national level
(National Centre for Disease Control, Directorate General of Health Services), state level
with special emphasis on the selected hospitals’ catchment areas, and at the district level for
the selected hospital areas. The data collected will include: number of suspected dengue
cases and the number of laboratory-confirmed dengue cases tabulated according to year,
state, region, severity, fatality rate, reported site (private or public, hospital or ambulatory,
location), age, gender and type of dengue virus and infection type (primary vs secondary),
if possible.
Aggregate cost of dengue in India
Combining the information from surveillance systems (reported dengue cases by age, year
and region) with the expansion factors generated through the Delphi process can give the
projected numbers of dengue cases in India. Accordingly, we will compute the aggregate
cost of hospitalized cases by multiplying the average number of hospitalized cases by the
average cost of a hospitalized episode (with disaggregation according to setting and age if the
data allows); the same approach will be used to compute the ambulatory services cost. The
overall cost will be computed using the weighted average cost of child and adult patients.
9
Discussion
The methodology discussed in this paper should be helpful in generating data and information
to support dengue policies in India. The investigators will estimate the proportion of patients
with dengue misdiagnosed at discharge as febrile illnesses other than dengue. In addition, we
will compute the in-hospital dengue case-fatality rate and the seasonal variation of dengue
infection by year for all the sites and for individual sites. And, finally, this methodology can
help build a mathematical model of the burden of dengue in different regions of India
using the proportion of the population served in each site, and the estimated proportion of
population seeking admission in the study’s selected medical college hospitals.
Acknowledgments
The authors thank Vivek Adish, Rohit Arora, Jeremy Brett, Meenu Maheshwari and Josemund
Menezes for their valuable comments on the study design during a planning workshop in New
Delhi; Josemund Menezes and Eduardo Undurraga for important background information
on dengue; and Clare Hurley for editorial assistance.
References
[1] Gubler DJ. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem
in the 21st century. Trends Microbiol. Feb 2002; 10(2): 100-103.
[2] Ooi EE, Gubler DJ. Dengue in Southeast Asia: epidemiological characteristics and strategic challenges
in disease prevention. Cad Saude Publica. 2009; 25(Suppl 1): S115-124.
[3] World Health Organization. Dengue haemorrhagic fever: diagnosis, treatment, prevention and control.
3rd edn. Geneva: WHO, 2009.
[4] World Health Organization, Regional Office for South-East Asia. Comprehensive guidelines for prevention
and control of dengue and dengue haemorrhagic fever. Revised and expanded edition. New Delhi:
WHO-SEARO, 2011.
[5] Ooi E-E, Gubler DJ, Nam VS. Dengue research needs related to surveillance and emergency response.
Geneva: World Health Organization, 2007.
[6] Beatty ME, Beutels P, Meltzer MI, et al. Health economics of dengue: a systematic literature review
and expert panel’s assessment. Am J Trop Med Hyg. 2011 Mar; 84(3): 473-488.
[7] Halstead SB. Pathogenesis of dengue: challenges to molecular biology. Science. 1988 Jan 29; 239(4839):
476-481.
[8] Isturiz RE, Gubler DJ, Brea del Castillo J. Dengue and dengue hemorrhagic fever in Latin America and
the Caribbean. Infect Dis Clin North Am. Mar 2000; 14(1):121-140, ix.
[9] World Health Organization. Dengue hemorrhagic fever: diagnosis, treatment, prevention and control.
2nd. Edition. Geneva: World Health Organization, 1997.
10
[10] Gupta V, Yadav TP, Pandey RM, et al. Risk factors of dengue shock syndrome in children. Journal of
Tropical Pediatrics. 2011; 57(6): 451-456.
[11] Priyadarshini D, Gadia RR, Tripathy A, et al. Clinical findings and pro-inflammatory Cytokines in dengue
patients in Western India: a facility-based study. PLoS One. 2010; 5(1): e8709.
[12] Anoop M, Issac A, Mathew T, et al. Genetic characterization of dengue virus serotypes causing
concurrent infection in an outbreak in Ernakulam, Kerala, South India. Indian J Exp Biol. Aug 2010;
48(8): 849-857.
[13] Cecilia D, Kakade MB, Bhagat AB, et al. Detection of dengue-4 virus in pune, western india after an
absence of 30 years--its association with two severe cases. Virol J. 2011; 8(1): 46.
[14] Guzman MG, Kouri G. Dengue: an update. Lancet Infect Dis. 2002 Jan; 2(1): 33-42.
[15] Malavige GN, Fernando S, Fernando DJ, Seneviratne SL. Dengue viral infections. Postgrad Med J. Oct
2004; 80(948): 588-601.
[16] Halstead SB. Dengue. Lancet. 2007 Nov 10; 370(9599): 1644-1652.
[17] Sangkawibha N, Rojanasuphot S, Ahandrik S, et al. Risk factors in dengue shock syndrome: a prospective
epidemiologic study in Rayong, Thailand. I. The 1980 outbreak. Am J Epidemiol. 1984 Nov; 120(5):
653-669.
[18] Makino Y, Tadano M, Saito M, et al. Studies on serological cross-reaction in sequential flavivirus
infections. Microbiol Immunol. 1994; 38(12): 951-955.
[19] Guzman MG. Global voices of science. Deciphering dengue: the Cuban experience. Science. 2005
Sep 2; 309(5740): 1495-1497.
[20] Guzman MG, Kouri G, Halstead SB. Do escape mutants explain rapid increases in dengue case-fatality
rates within epidemics? Lancet. 2000 May 27; 355(9218): 1902-1903.
[21] Guzman MG, Kouri G, Valdes L, et al. Epidemiologic studies on dengue in Santiago de Cuba, 1997.
Am J Epidemiol. 2000 Nov 1; 152(9): 793-799; discussion 804.
[22] Anantapreecha S, Chanama S, A-nuegoonpipat A, et al. Serological and virological features of dengue
fever and dengue haemorrhagic fever in Thailand from 1999 to 2002. Epidemiol Infect. 2005 Jun;
133(3): 503-507.
[23] Chaturvedi UC, Nagar R. Dengue and dengue haemorrhagic fever; Indian perspective. Journal of
Biosciences. 2008; 33(4): 429-441.
[24] Yeh WT, Chen RF, Wang L, Liu JW, Shaio MF, Yang KD. Implications of previous subclinical dengue
infection but not virus load in dengue hemorrhagic fever FEMS. Immunology and Medical Microbiology.
2006; 48(1): 84-90.
[25] Jain A, Chaturvedi UC. Dengue in infants: an overview. FEMS Immunology and Medical Microbiology.
2010 Jul 1; 59(2):119-130.
[26] Dar L, Broor S, Sengupta S, Xess I, Seth P. The first major outbreak of dengue hemorrhagic fever in
Delhi, India. Emerg Infect Dis. 1999 Jul-Aug; 5(4): 589-590.
[27] Vijayakumar TS, Chandy S, Sathish N, Abraham M, Abraham P, Sridharan G. Is dengue emerging as a
major public health problem? Indian Journal of Medical Research. 2005; 121(2): 100-107.
11
[28] Ranjit S, Kissoon N. Dengue hemorrhagic fever and shock syndromes. Pediatr Crit Care Med. 2011
Jan; 12(1): 90-100.
[29] Addlakha R. State legitimacy and social suffering in a modern epidemic:a case study of dengue
haemorrhagic fever in Delhi. Indian Sociology. 2001; 35(2): 151-179.
[30] Chandralekha, Gupta P, Trikha A. The north Indian dengue outbreak 2006: a retrospective analysis of
intensive care unit admissions in a tertiary care hospital. Trans R Soc Trop Med Hyg. 2008 Feb; 102(2):
143-147.
[31] Gupta E, Dar L, Kapoor G, Broor S. The changing epidemiology of dengue in Delhi, India. Virol J.
2006; 3: 92.
[32] Sinha N, Gupta N, Jhamb R, Gulati S, Kulkarni Ajit V. The 2006 dengue outbreak in Delhi, India. J
Commun Dis. 2008 Dec; 40(4): 243-248.
[33] Raheel U, Faheem M, Riaz MN, et al. Dengue fever in the Indian subcontinent: and overview. The
Journal of Infection in Developing Countries. 2011; 5(4): 239-247.
[34] Kumaria R. Correlation of disease spectrum amoung four dengue serotypes: a five years hospital based
study from India. Brazilian Journal of Infectious Diseases. 2010; 14(2): 141-146.
[35] Gunasekaran P, Kaveri K, Mohana S, et al. Dengue disease status in Chennai (2006-2008): a retrospective
analysis. Indian J Med Res. 2011 Mar; 133(3): 322-325.
[36] Hati AK. Dengue serosurveillance in Kolkata, facing an epidemic in West Bengal, India. J Vector Borne
Dis. 2009 Sep; 46(3): 197-204.
[37] Kukreti H, Mittal V, Chaudhary A, et al. Continued persistence of a single genotype of dengue virus
type-3 (DENV-3) in Delhi, India since its re-emergence over the last decade. Journal of Microbiology,
Immunology, and Infection. 2010 Feb; 43(1): 53-61.
[38] Kumar A, Rao CR, Pandit V, Shetty S, Bammigatti C, Samarasinghe CM. Clinical manifestations and
trend of dengue cases admitted in a tertiary care hospital, Udupi district, Karnataka. Indian Journal of
Community Medicine 2010 Jul; 35(3):386-390.
[39] Gupta P, Khare V, Tripathi S, et al. Assessment of World Health Organization definition of dengue
hemorrhagic fever in North India. J Infect Dev Ctries. 2010 Mar; 4(3): 150-155.
[40] Chhina DK, Goyal O, Goyal P, Kumar R, Puri S, Chhina RS. Haemorrhagic manifestations of dengue
fever and their management in a tertiary care hospital in north India. Indian Journal of Medical Research.
2009; 129(6):718-720.
[41] Bhaskar ME, Moorthy S, N.S K, Arthur P. Dengue haemorrhagic fever among adults-An observational
study in Chennai, south India. Indian Journal of Medical Research. 2010; 132(6): 738-740.
[42] Hati AK. Studies on dengue and dengue haemorrhagic fever (DHF) in West Bengal State, India. J
Commun Dis. 2006 Mar; 38(2): 124-129.
[43] Zaki SA, Shanbag P. Clinical manifestations of dengue and leptospirosis in children in Mumbai: an
observational study. Infection. 2010; 38: 285-291.
[44] Kishore J, Singh J, Dhole TN, Ayyagari A. Clinical and serological study of first large epidemic of dengue
in and around Lucknow, India, in 2003. Dengue Bulletin. 2006; 30: 72-79.
12
[45] Sharma SK. Entomological investigations of DF/DHF outbreak in rural areas of Hissar district, Haryana,
India. Dengue Bulletin. 1998; 22: 36-41.
[46] Kumar A, Sharma SK, Padbidri VS, Thakare JP, Jain DC, Datta KK. An outbreak of dengue fever in rural
areas of northern India. J Commun Dis. Dec 2001 ;33(4): 274-281.
[47] Ukey PM, Bondade SA, Paunipagar PV, Powar RM, Akulwar SL. Study of seropervalence of dengue
fever in central India. Indian J Community Med. 2010; 35(4): 517-519.
[48] Paramasivan R, Dhananjeyan KJ, Leo SV, et al. Dengue fever caused by dengue virus serotype-3
(subtype-III) in a rural area of Madurai district, Tamil Nadu. Indian J Med Res. 2010 Sep; 132:
339-342.
[49] Lamont J. Dengue in Delhi: disease and authority in India. Financial Times. 2010. Available from: http://
blogs.ft.com/beyond-brics/2010/09/15/dengue-in-delhi-disease-and-authority-in-india/#axzz1iYrfxN3J
- accessed 15 October 2011.
[50] Bigongiari J. Dengue fever cases in India continue to climb. Vaccine News Daily 2010. http://
vaccinenewsdaily.com/news/217977-dengue-fever-cases-in-india-continue-to-climb - accessed 15
October 2011.
[51] Srivastava M, Gale J. In India, Dengue Fever Stalks the Affluent. Bloomberg Businessweek 2010. http://
www.businessweek.com/magazine/content/10_39/b4196013896421.htm – accessed on 15 October
2011.
[52] Tanner L, Schreiber M, Low JG, et al. Decision tree algorithms predict the diagnosis and outcome of
dengue fever in the early phase of illness. PLoS Negl Trop Dis. 2008; 2(3): e196.
[53] Arya SC, Agarwal N. Thrombocytopenia progression in dengue cases during the 2010 outbreak in
Indian capital metropolis. Platelets. 2011; 22(6): 476-7.
[54] Chakravarti A, Gur R, Berry N, Mathur MD. Evaluation of three commercially available kits for serological
diagnosis of dengue haemorrhagic fever. Diagn Microbiol Infect Dis. 2000 Apr; 36(4): 273-274.
[55] Innis BL, Nisalak A, Nimmannitya S, et al. An enzyme-linked immunosorbent assay to characterize
dengue infections where dengue and Japanese encephalitis co-circulate. Am J Trop Med Hyg. 1989
Apr; 40(4): 418-427.
[56] Henchal EA, Polo SL, Vorndam V, Yaemsiri C, Innis BL, Hoke CH. Sensitivity and specificity of a universal
primer set for the rapid diagnosis of dengue virus infections by polymerase chain reaction and nucleic
acid hybridization. Am J Trop Med Hyg. 1991 Oct; 45(4): 418-428.
[57] Kumar A, Pandit VR, Shetty S, Pattanshetty S, Krish SN, Roy S. A profile of dengue cases admitted to
a tertiary care hospital in Karnataka, southern India. Trop Doct. 2010; 40:45-46.
[58] Murtola TM, Vasan SS, Puwar TI, et al. Preliminary estimate of immediate cost of chikungunya and
dengue to Gujarat, India. Dengue Bulletin. 2010; 34: 32-39.
[59] Garg P, Nagpal J, Khairnar P, Seneviratne SL. Economic burden of dengue infections in India. Trans R
Soc Trop Med Hyg. Jun 2008; 102(6): 570-577.
[60] Bhavsar AT, Shepard DS, Suaya JA, Mafowosofo M, Hurley CL, Howard MW. A private hospital based
study assessing knowledge attitudes practices and cost associated with dengue illness in Surat, India.
Dengue Bulletin. 2010; 34: 54-64.
13
[61] Anderson KB, Chunsuttiwat S, Nisalak A, et al. Burden of symptomatic dengue infection in children at
primary school in Thailand: a prospective study. Lancet. 2007 Apr 28; 369(9571): 1452-1459.
[62] Kohli VK. Entomological monitoring, sero-surveillance and preventive measures against Dengue and
Chikungunya in Ahmedabad. In: 1st Symposium on the Burden of Neglected Diseases; Vasan SS,
Mavalankar DV, editors; 10 Sep 2008, Ahmedabad, India.
[63] Suaya JA, Shepard DS, Siqueira JB, et al. Cost of dengue cases in eight countries in the Americas and
Asia: a prospective study. Am J Trop Med Hyg. May 2009; 80(5): 846-855.
[64] Srikiatkhachorn A, Rothman AL, Gibbons RV, et al. Dengue--how best to classify it. Clin Infect Dis.
2011 Sep; 53(6): 563-567.
[65] World Health Organization. Expert committee on biological standardization. Geneva: WHO, 2011.
[66] World Health Organization. WHO recommended surveillance standards. Geneva: WHO, 1999.
[67] Shepard DS, Hodgkin D, Anthony YE. Analysis of hospital costs a manual for managers. Geneva: World
Health Organization, 2000.
[68] National Vector Borne Disease Control Programme. Sentinel surveillance hospitals. Delhi: Government
of India; 2011. http://nvbdcp.gov.in/Doc/SSH-2011.pdf. - accessed: Nov 21, 2011.
[69] National Vector Borne Disease Control Programme. Apex referral laboratories Delhi: Government
of India; 2011. http://nvbdcp.gov.in/Doc/APEX-REFERRAL-LABORATORIES.pdf. Accessed: Nov 21,
2011.
14
Identifying and visualizing spatial patterns and
hot spots of clinically-confirmed dengue fever cases
and female Aedes aegypti mosquitoes in
Jeddah, Saudi Arabia
Hassan Muhsan Khormi#a,b & Lalit Kumara
Ecosystem Management, School of Environmental and Rural Sciences, Faculty of Arts and Sciences,
University of New England, Armidale, NSW 2351, Australia
a
Department of Geography, Umm Al-Qura University, Makkah, Saudi Arabia.
b
Abstract
Understanding the distribution of dengue fever in time and space is the foundation for its control and
management programmes. Different technologies, especially the Geographic Information System
(GIS) and its tools and methods, have been used to illustrate and visualize the prevalence of some
mosquito-borne diseases and abundance of their vectors. The aim of this study was to illustrate
the spatial distribution and spatial pattern of this disease and female Aedes aegypti mosquitoes in
the epidemic-prone area of Jeddah, and also to show the hot spot districts with the highest risk
levels. The study was conducted in Jeddah county, Saudi Arabia. The clinically-confirmed cases
registries of dengue fever have been continuously and systematically collected since 2006 by the
Dengue Fever Operation Room of Jeddah Health Affairs. The computerized databases of these two
government departments have recorded weekly notifications of dengue fever cases and its vector
(female Aedes mosquito). The female Aedes mosquito counts and identification were provided by
the laboratory of mosquito, which belongs to the Jeddah Municipality. Two GIS techniques were
used to achieve the aims of this study. The multi-distance spatial cluster (Ripley’s K-function) was
used to estimate the spatial pattern and distribution while the Getis-Ord Gi* statistic was used
to model and visualize the hot spots and the risk models. The results showed that the spatial
patterns and distribution of dengue fever cases from 2006 to 2009 were clustered at multiple
distances with statistically significant clustering. They also showed that most Aedes mosquitoes
were clustered while some of them were dispersed at larger distances, especially in 2007, 2008,
2009 and 2010. Also, areas with various risk levels of dengue fever and its vector were identified
in different geographical locations (districts) for different epidemic years using the Getis-Ord Gi*.
Identifying dengue fever and its vector cluster and hot spots can be greatly enhanced through the
use of a variety of analytical techniques that are available in the Geographic Information System.
Getis-Ord Gi* and multi-distance spatial cluster (Ripley’s K-function) can be implemented as
routine procedures along with dengue fever control and prevention programmes.
Keywords: GIS; Aedes; Dengue fever; Hot spots; Risk levels; Spatial pattern; Jeddah.
#
E-mail: [email protected], [email protected]
15
Spatial patterns and hot spots of dengue fever and Aedes aegypti
Introduction
Dengue fever (DF) is a mosquito-borne viral illness. It is caused by one of the four serotypes of
the dengue virus, which belongs to the family Flaviviridae, and is predominantly transmitted
by Aedes mosquitoes.[1] An empirical model shows that around 35% of the world’s population
(2.5 billion people) live in countries with risk of dengue.[2,3,4] Among the mosquito-borne
diseases in Saudi Arabia, mainly Rift Valley fever, malaria and dengue, the latter ranks as of
the highest concern for public health in the country in general and in Jeddah in particular.
[5,6]
Many other regions are undergoing unplanned urban growth and are lacking water
supply and proper drainage and waste disposal, which have created suitable conditions for
mosquitoes to breed.[7]
Understanding the distribution of dengue incidence in time and space can be a foundation
for disease control and management programmes. Knowledge of when and where cases of
dengue fever occur will enable the formulation of disease causation hypotheses for cases
with unknown or poorly characterized etiology, identification of disease-risk areas and a
design of efficient surveillance and control programmes.[8]
Recently, different technologies, especially the Geographic Information System (GIS) and
its tools and methods, have been used to illustrate and visualize the prevalence of some of
the mosquito-borne diseases and the abundance of their vectors.[9-17] For example, Ernst et
al.[18] used GIS to illustrate the malaria hot spot areas in highland Kenya. They found that the
knowledge of hotspot areas of high malaria incidence would allow for focused preventive
interventions in resource-poor areas, particularly if the hotspot areas can be discerned during
non-epidemic periods and predicted by ecological factors.
GIS methods of spatial distribution and spatial pattern can help identify the hot spot and
cold spot areas, clustered or dispersed patterns of DF cases and their transmitters. GIS and
its statistical methods can play an important role in formulating dengue control activities,
assessing changes over time in DF transmission and determining resources to control DF
prevalence, particularly in high or persistent locales of DF transmission, directions and spatial
pattern.[19-22]
For Saudi Arabia, to date, there is no published study that used GIS and its spatial
statistical methods to identify and visualize areas with hot spots, distribution (clustered or
dispersed) and spatial pattern (the way in which the distribution of clinically-confirmed cases
of dengue and its vector (Aedes aegypti) are found in different districts). The aim of this study
was to illustrate the spatial distribution and spatial pattern of this disease and female Aedes
mosquitoes in the epidemic-prone area of Jeddah and also to show the hot spot districts with
the highest risk levels. Two GIS techniques were used to achieve the aims of this study. The
multi-distance spatial cluster (Ripley’s K-function) was used to estimate the spatial pattern
and distribution while the Getis-Ord Gi* statistic was used to model and visualize the hot
spots and the risk models.
16
Material and methods
Study site
The study was conducted in Jeddah county (21°32’33”N and 39°10’22”E), that is, the
largest city in Makkah province, Saudi Arabia. It is situated on the coast of the Red Sea and,
as home to about 3.5 million people, is considered to be the major urban area of western
Saudi Arabia. It is the main gateway to Mecca and Al Medina, regarded as the two holiest
sites in Islam. Jeddah has 13 sub-municipalities and 111 districts. The study area is around
1100 km² and extends from Al Janoub in the southern part of Jeddah to Dhahban in the
northern part (Figure 1). According to Jeddah Health Affairs, Ministry of Health, this area
reports the highest incidence of mortality and morbidity in Jeddah.
Data sources, cleaning and organizing
Daily mosquito samples are acquired by black hole traps and these are returned to the
mosquito laboratory for filtering and sorting according to species, sex, date of collection,
coordinates and number of mosquitoes for each location. According to Aburas,[23] black hole
traps were considered the most efficient traps for the study area. From the mosquitoes that
were collected, only female Aedes aegypti were used in the analysis in this research. The
female Aedes aegypti mosquito counts and identification were provided by the laboratory
of mosquito, which belongs to the Jeddah Municipality. For the capture of mosquitoes,
504 black hole traps have been in operation since 2006. These traps were distributed
geographically based on population density and different environmental factors (Figure 2)
and captured mosquitoes by producing carbon dioxide. The clinically-confirmed cases
registries of dengue fever have been collected since 2006 continuously and systematically by
the Dengue Fever Operation Room of Jeddah Health Affairs and by the Jeddah Municipality.
The computerized databases provided by these two government departments have recorded
weekly notifications of dengue fever cases and its vector (Aedes aegypti mosquitoes), including
age, sex, nationality, district, coordinates and the week of disease onset for each case. The
collected data were entered into Excel files to remove the duplicated and redundant data,
fill the missing values, transform some coordinates from degrees, minutes and seconds to
decimal degrees and convert dates to weeks for each year of epidemic. Using ArcCatalog
v.9.3.1, point shape files of clinically-confirmed cases and female Aedes mosquitoes were
created and projected to WGS 1984 UTM Zone 37N. The base map of the districts was
digitized and projected to the same projection using Arc Map v.9.3.1. For the base map of
the districts, the database included the number of cases in each district for different years
and the number of mosquitoes captured by the black hole traps from week 23 of 2006 to
week 52 of 2010.
17
Figure 1: The study area in Jeddah, Saudi Arabia
18
Figure 2: Location of black hole traps in the study area of Jeddah
Location of black hole traps
19
Data analysis
Spatial pattern
Spatial pattern methods, such as kernel estimation, multi-distance spatial cluster (Ripley’s
K-function), average nearest neighbour and spatial autocorrelation (Moran’s I), can be used
to identify the key areas of mosquito-borne diseases. Many studies have used some of these
methods to illustrate the spatial patterns of dengue fever and Aedes mosquitoes. For example,
kernel estimation was used to analyse the spatial pattern of dengue and its vector in Nova
Iguacu, Rio de Janeiro.[24] The results of this study showed five areas with high and medium
density of positive Aedes mosquitoes breeding sites. Also, it highlighted small block clusters
with high larval density and recommended this method for dengue fever surveillance.
In this study, the method chosen to analyse the spatial patterns of dengue and Aedes
mosquitoes was the multi-distance spatial cluster (Ripley’s K-function) (Equation 1). This
method is useful for point pattern analysis and also it is the best method to illustrate the
point pattern at multiple distances compared with others mentioned above. In this study,
Ripley’s K-function was used to determine whether the distribution of clinically-confirmed
dengue cases and also Aedes mosquitoes were clustered or dispersed at multiple different
distances. The inputs of values for this analysis were based on data from individual trap
locations and individual case locations. The outputs were represented as graphic models
for the epidemic years in Jeddah. The graphs contain details of expected K and observed K
that were calculated using the following K-function:
(Equation 1)
Where d is the distance, n is equal to the total number of clinically-confirmed DF
cases, A represents the total of the study area and ki,j is a weight, which (if there is no edge
correction) is 1 when the distance between i and j is less than or equal to d and 0 when the
distance between i and j is greater than d. When edge correction is applied, the weight of
k(i,j) is modified slightly.
Tables were produced to show the observed K minus the expected K values (DiffK),
and also the low confidence envelope values (LowConEn) and high confidence envelope
values (HiConEn).[25,26] For Ripley’s K-function, Boots and Getis[27] and Mitchell[26] illustrated
that if the observed K value is larger than the expected K value for a particular distance, the
distribution is more clustered than a random distribution at that distance (scale of analysis).
If the observed K value is smaller than the expected K, the distribution is more dispersed
than a random distribution at that distance. Also, if the observed K value is larger than the
high confidence envelope (HiConfEnv) value, spatial clustering for that distance is statistically
20
significant. If the observed K value is smaller than the low confidence envelope (LwConfEnv)
value, spatial dispersion for that distance is statistically significant.
The neighbourhood sizes and analysis of the datasets of clinically-confirmed DF cases and
female Aedes mosquitoes were put through 20 iterations for clustering to optimize accuracy.
The confidence envelopes were computed at 99% confidence interval (CI), and weight fields
were selected according to the layer datasets. For example, the number of cases in each
district was used as a weight field when the method was used to analyse the spatial pattern
of confirmed cases of dengue fever, while the number of female Aedes mosquitoes for each
trap was used as a weight field when the method was used to analyse the spatial pattern of
female Aedes mosquitoes. Simulated outer boundary values were selected as a boundary
correction method because they simulated points outside the study area and because the
simulated points were the mirrors of points across the study area boundary.
Hot spot analysis
Knowledge about the extent of spatial association in mosquito-borne disease data such
as clinically-confirmed cases of dengue fever and its vector is essential for the controlling,
managing and monitoring purposes.[28] Different methods can be used to identify and visualize
the spatial association. However, many local statistical methods, such as geographicallyweighted Poisson regression (GWPR), Getis-Ord Gi* statistics, local indicators of spatial
association (LISA) statistics, multi-logistic regression, local Moran’s I and Geary’s, have been
developed to measure the spatial dependency with its neighbours specified by sample
data of a study area. Therefore, these types of statistics can be used easily to identify and
visualize areas of hot spots and cold-spots.[4,12,27,29] For instance, Wu et al.[4] used multiple
logistic regression to explore threshold values of the imported incidence, household vector
recovery rate, annual rainfall, and higher elderly and aborigine population in discriminating
higher and lower risks of dengue fever epidemics in Taiwan.
In this study, the Getis-Ord Gi* statistic (Equation 2) was applied to examine the local
level of spatial cluster in order to identify and visualize districts where the values of dengue
fever rate and adult female Aedes mosquitoes were both extreme and geographically
homogeneous. This type of analysis is particularly helpful for resource allocation purposes.
It identifies so-called dengue and adult female Aedes mosquito hot spots, where the value
of the index is extremely pronounced across Jeddah districts. First, the conceptualization of
spatial relationships that specified how relationships between dengue fever case locations
and also female Aedes locations was calculated using the fixed-distance band. The fixeddistance band included the locations of DF cases inside the boundary of the study area,
and it excluded everything outside that boundary. Also, it was used because it was generally
more appropriate than the inverse distance conceptualization methods.[26] Secondly, the
Euclidian distance was used as the distance method. Since the number of black hole traps
differed from district to district, the number of mosquitoes was divided by the number of
21
traps for each district, giving us the average number of mosquitoes per trap. The output of
this analysis was a z-score and p-value for each district in Jeddah. The districts with high
z-scores and small p-values indicated a spatial clustering of a high level of hot spots of DF
and adult female Aedes mosquitoes, and the districts with low z-scores and small p-values
indicated a spatial clustering of a low level of hot spots of DF and Aedes mosquitoes.
(Equation 2)
Where xj is the attribute value for feature j, wi,j is the spatial weight between i and j,
and n is equal to the total number of features.
Results
Spatial pattern of dengue fever cases
Table 1 and Figure 3 give summary statistics of K-function results, calculated by using the multidistance spatial cluster (Ripley’s K-function) to illustrate the spatial patterns and distribution
of dengue fever cases over four years.
In general, the results (Table 1 and Figure 3) showed that the spatial patterns and
distribution of dengue cases from 2006 to 2009 were clustered at multiple distances because
the observed K values were larger than the expected K values at different distances with
statistically significant clustering. For example, in 2006, the observed K value (min distance
≈ 4966 m and max distance ≈ 25 486 m) was larger than the expected K value (min
distance ≈ 917 m and max distance ≈ 18 395 m). As a result, the distribution of dengue
fever cases in this year was more clustered than a random distribution at those distances.
Also, the mean distance of the observed K (≈18 592 m) was larger than the mean distance
of high confidence (≈ 9877 m), which confirmed that the spatial clustering at different
multiple distances in 2006 was statistically significant (Table 1 and Figure 3(a)). Dengue fever
cases were more clustered in 2006 and 2008 as compared to other years due to the larger
differences between the observed K values and expected K values when using the maximum
distances (see shaded region in Figure 3).
Spatial pattern of adult female Aedes aegypti mosquitoes
Table 2 and Figure 4 show that most Aedes mosquitoes were clustered; however, some
of them were dispersed at larger distances, especially in 2007, 2008, 2009 and 2010.
According to Table 2, in 2006, the observed K (mean distance ≈ 19 200 m) was larger than
22
Table 1: Summary statistics of K-function results that applied to DF cases in four different
years (the bold numbers are referred to in the text)
Dengue fever clinically-confirmed cases
Years
Expected K
Observed K
Diff K
Low Con Env
High Con Env
Min
Max
Mean
Std
2006
917
18395
9631
5289
2007
550
11016
5783
3176
2008
604
12095
6350
3487
2009
1024
20487
10755
5906
2006
4966
25486
18592
5907
2007
2643
20802
13336
5465
2008
3084
22321
14440
5791
2009
4240
26012
18907
6469
2006
4049
10636
8961
1654
2007
2093
9817
7552
2373
2008
2479
10292
8090
2400
2009
3216
10268
8151
1952
2006
947
16242
9153
4653
2007
611
12660
6966
3677
2008
877
15338
8540
4400
2009
1007
16975
9616
4872
2006
1147
17309
9877
4948
2007
948
14168
7732
4002
2008
967
16195
9002
4645
2009
1098
17890
10159
5142
23
Table 2: Summary statistics of K-function results that applied to adult female Aedes
mosquitoes in five different years (the bold numbers are referred to in the text)
Adult female Aedes mosquitoes
Years
Expected K
Observed K
Diff K
Low Con Env
High Con Env
24
Min
Max
Mean
Std
2006
956
19 137
10 047
5517
2007
1422
28 457
14 940
8204
2008
1464
29 280
15 372
8441
2009
1411
28 238
14 825
8141
2010
1463
29 279
15 371
8441
2006
6251
24 933
19 207
5335
2007
4867
25 618
19 625
6219
2008
4581
25 756
19 646
6444
2009
3768
24 871
17 943
6451
2010
4262
24 693
17 892
6131
2006
5294
11 943
9160
1959
2007
–2839
7855
4684
3266
2008
–3523
7638
4274
3402
2009
–3367
6042
3118
2795
2010
–4586
5810
2520
3151
2006
2132
18 214
12 141
4817
2007
4320
25 184
18 764
6262
2008
3712
24 961
18 004
6474
2009
3372
22 510
15 848
5741
2010
3644
24 035
17 039
6096
2006
6213
24 794
18 594
5188
2007
5086
25 631
19 793
6043
2008
4571
25 611
19 363
6359
2009
4638
24 830
17 938
6167
2010
4335
24 836
18 201
6140
Figure 3: Measure of dengue fever clinically-confirmed cases at multi-distances from
2006 to 2009. If the observed K value is larger than the expected K value for a particular
distance, the distribution is clustered. If the observed K value is larger than the high
confidence envelope (HiConfEnv) value, spatial clustering for that distance is statistically
significant. If the observed K value is smaller than the expected K, the distribution is more
dispersed than a random distribution at that distance
the expected K (mean distance ≈ 10 000 m). Also, Figure 4(a) illustrates that the highest
number of clustering occurred at distances around 8600 m, and the clustering was also
statistically significant around this distance because the observed K was larger than the high
confidence envelope (HiConEnv). From about 950 to about 4780 m, the mosquito spatial
clustering was not statistically significant. In 2007, the Aedes mosquitoes were clustering
from about 1400 m to around 24 500 m (see Figure 4(b)); after that, they were dispersed.
Since the observed K values at multiple different distances were smaller than the high
confidence envelope (HiConEnv) values, the spatial clustering and spatial dispersion were
not statistically significant.
25
Figure 4: Measure of adult female Aedes mosquitoes at multi-distances from 2006 to
2010. If the observed K value is larger than the expected K value for a particular distance,
the distribution is clustered. If the observed K value is larger than the high confidence
envelope (HiConfEnv) value, spatial clustering for that distance is statistically significant.
If the observed K value is smaller than the expected K, the distribution is more dispersed
than a random distribution at that distance
26
In 2008, most of the female Aedes mosquitoes were clustered between the distances
around 1460 m and around 24 880 m, and the spatial clustering was statistically significant,
while some of them started to be dispersed after about 24 880 m, and the spatial dispersion
was not statistically significant (see Figure 4(c)). Figure 4(d) shows that the observed K
values were larger than the expected K values at most of the multiple different distances,
which shows that the distribution of female Aedes mosquitoes was clustering with more
than a random distribution, but that after about 24 000 m the distribution of female Aedes
mosquitoes was dispersed with no significance. In 2010, the distribution of mosquitoes was
clustered from about 1460 m to about 21 950 m; after that distance (≈21 950 m), they
started to be dispersed. The spatial clustering and dispersion were not statistically significant
in this year.
Hot spot analysis
Dengue fever hot spot detection
Areas with various risk levels of dengue fever and its vector were identified in different
geographical locations (districts) for different epidemic years using the Getis-Ord Gi‫٭‬
(Figure 5). According to Figure 5 (a), districts such as Al-Balad, Al-Kandarah, Al-Ammareyyah,
Al-Mahgar, Al-Sabeel, Al-Hendaweyyah, Al-Thagur, Guleel and Al Nazalah-Al Yamaneyyah
had the highest risk level for dengue fever, with 654 clinically-confirmed cases (districts
shaded in dark red). These accounts for about 14% of the districts under investigation and
have around 13% (about 354 792) of the population and an area of about 27 km². These
districts had the highest Z scores (3.18 to 6.49), and the results showed the most intense
clustering of high values; therefore, these areas were identified as the hottest spots. The
results also showed that around 11% (≈ 80 km²) of Jeddah districts were in a high-risk level
(second level), with 207 clinically-confirmed cases of dengue. Because they had positive Z
scores (1.14 to 3.17), the spatial clustering of the clinically-confirmed cases in these areas
was statistically significant and they were identified as hot spots. Of all the districts in the
study area, about 67% (≈ 900 km²) were cold-spot districts with negative Z score values.
Around 94 % (≈ 878 km²) of these districts had the low and lowest levels of risk with 2 as
the mean number of clinically-confirmed cases, and around 6% (≈ 23 km²) with 9 as the
mean number of cases in 2006.
In 2007, there was a decrease in the percentage of districts in the highest risk level (from
14% to 5%) and there was an increase in the percentage of districts in the high level of risk
(from 11% to 28%). However, in terms of area, there was a decrease in the total area of the
highest risk level from about 66 km² in 2006 to about 54 km² in 2007, and there was an
increase in the total area of the high-risk level from about 79 km² to about 130 km². Both
these groups of districts had positive Z scores, which identified these areas as hot spots.
Al-Rehab, Al-Azizeyyah, Al-Marwah, Al-Safa, Al-Rabwah and Al-Faysaleyyah were identified
as the highest risk level, with about 25% of clinically-confirmed cases of dengue fever. Those
districts cover around 54 km² and they have a population of around 618 501. Note that the
27
hot spots were different from those in 2006. In 2008, about 13% of Jeddah districts had the
highest risk level (Z scores between 4.28 and 6.21). All the districts (14) that were identified
as hot spots in that year were also identified as hot spots in 2006. Additionally, those districts
contained around 42% of clinically-confirmed cases of dengue fever. In 2009, the number of
districts identified as hot spots increased as compared to 2006, 2007 and 2008; as a result,
about 18% of Jeddah districts entered the highest risk level (hottest spots) with Z scores from
2.75 to 4.88, and around 14% (16 districts) were indicated as high-risk areas with Z scores
between 1.34 to 2.74. Additionally, the percentage of clinically-confirmed DF cases in the
hot spot districts was around 72%. In 2010, 37 districts (about 33% of Jeddah districts) were
identified as hot spots (Z scores between 1.46 and 5.24). These districts contained the largest
numbers of infected people; with a total of 1960 clinically-confirmed cases (about 77% of
clinically-confirmed DF cases). The areas in the highest level of risk had 46% of the total
percentage of clinically-confirmed cases in the hot spot districts. Also, Figure 5 (e) illustrates
that about 52% of districts were cold spots and in the low or lowest risk levels.
Adult female Aedes aegypti mosquitoes hot spot detection
The model in Figure 6 shows the locations with significant Getis-Ord Gi* statistics and classifies
those locations by risk levels. The dark red districts and light red districts were indications of
the highest and high spatial clusters with the highest and high risk levels respectively. In 2006,
most of the districts that had the highest and high risk levels of dengue fever prevalence also
were indicated as high and the highest risk levels of mosquito abundance, especially in the
centre districts of Jeddah (see Figure 5 (a) and 6 (a)). The highest and high levels of abundance
of adult female Aedes mosquitoes (hot spots) were recorded in about 25% of Jeddah districts,
with around 71% of trapped mosquitoes, and Al Faihaa contained the maximum number
of adult Aedes mosquitoes in this year with 2478. The percentage of cold spot districts was
around 54, with negative Z scores that ranged from about –1.10 to about –0.07.
There was an increase in the percentage of districts that had the highest risk level from
about 16% in 2006 to about 18% in 2007; also there was an increase in the percentage of
districts that had the high risk level from about 9% in 2006 to about 13% in 2007, and all of
them were detected as hot spots because they had positive Z scores that ranged between
0.74 and 4.29 in 2006 and between 1.25 and 4.18 in 2007. In 2008, about 31% of Jeddah
districts were detected as hot spots with the highest and high risk level (Z scores from about
1.04 to about 5.11), and around 21% of Jeddah districts (around 191 km²) were detected
in moderate risk level while around 49% of Jeddah districts were detected as cold spots
with low or lowest risk levels. In 2009 and 2010, new districts in different parts of Jeddah
were detected with the highest and high risk levels of adult female Aedes mosquitoes for the
first time since 2006. In 2009, 27 districts were detected as hot spots with the highest and
high risk levels (Z scores that ranged from 1.01 to 5.59). Of those districts, about 19% were
identified with the highest risk level and about 81% with a high risk level.
28
Figure 5: Model of hot spot areas based on risk levels for dengue fever cases
Figure 6: Model of hot spot areas of female Aedes mosquito
29
The year 2010 represented an increase in the number of districts (57 districts, or about
51%) that were detected as hot spots due to the positive values of Z scores. Of those districts,
14 were in the highest level of risk, with 21% of total female Aedes mosquitoes, while 23
districts were in the high level of risk, with 38% of female Aedes mosquitoes trapped during
this year.
Discussion
Multi-distance spatial cluster analysis and hot spot analysis are valuable tools for studying
how spatial patterns and hot spots of dengue fever and its vector changed from 2006 to
2010 in Jeddah. This study has utilized GIS spatial analysis tools to integrate dengue fever
and female Aedes mosquitoes’ notification records and Jeddah districts for identifying and
visualizing the spatial patterns and hot and cold spots. The hot spots identified in these
analyses could explain the entire variance and they could predict risk in dengue fever
transmission. The study showed that the spatial distribution patterns of dengue fever and its
vector were significantly clustered. Hot spot analysis illustrated variation in the grouping of
dengue fever and female Aedes mosquitoes across the study area, and strongly confirmed
the visible pattern of districts.
From 2006 to 2010, we can see the hot spots of clinically-confirmed cases of dengue
fever and female Aedes aegypti mosquitoes concentrated in most of the districts that extended
between the latitudes 21°41’9.163”N and 21°24’35.675”N. These districts have limited safe
water, high population density, high building density and limited access to infrastructure. This
fact was reinforced by several studies,[5,24,30] where the authors found that Aedes mosquitoes
and dengue fever risk cases increase in areas with high human population density and high
concentrations of dwellings. Also, this study showed spatial heterogeneity in the risk areas of
dengue fever when using hot spot analysis. Most of the moderate risk-level districts in 2006
shifted to the highest or high risk levels in 2007, and some of the districts at a high risk level
in 2007 shifted to the highest risk level in 2008. Both of these shifts also occurred in 2009
and 2010. This data should provide insights for improving the DF surveillance system and
for control interventions in Jeddah.
In general, the association between the prevalence of dengue fever and the abundance
of Aedes mosquitoes is strong. For example, most of the clinically-confirmed DF cases were
recorded in the districts that had the highest or high risk levels of female Aedes mosquitoes.
In other words, most of the clinically-confirmed DF cases were recorded within the districts
that were identified as mosquito hot spots from 2006 to 2008, but in 2009 and 2010, the
situation was somewhat different. Some districts with negative Z scores (too small number
of mosquitoes), such as Al Balad, Al Hendaweyyah, Guleel, Al Thaalbah, Al Kandarah and
Betrumen, were observed with high and the highest risk levels of DF infection, with around
339 cases in 2009 and 771 cases in 2010. There are several plausible explanations for the
nearly simultaneous appearance of dengue fever cases in those districts. Firstly, the most
30
prevalent infected age groups were teenagers and adults, and about 91% of them were
between 15 to 60 years of age in 2009 and about 92% were between 15 to 60 years of age
in 2010. These groups are highly mobile, working and travelling outside of their districts
and visiting relatives and friends within the districts with a high density of female Aedes
mosquitoes. Secondly, most of the victims were non-Saudi, accounting for around 66% in
2009 and around 77% in 2010. These groups usually worked at construction sites, block
factories, animal fences, fuel stations, cars and tyres repair shops, farms and storages, which
are the major breeding sites. In 2009 and 2010, many of the female Aedes mosquitoes were
observed in districts that contained a high number of such sites. Additionally, the increase
of hot spots and distribution of female Aedes mosquitoes that were observed was due to
the high amount of rainfall that occurred in Jeddah during the winter season (November to
January), with around 90 mm in 2009 and around 111 mm in 2010. These levels were higher
than in 2006, 2007 and 2008 when the average rainfall was around 50 mm. This created
many hotbeds of reproduction of Aedes mosquitoes such as swamps and soil depressions
that retain water, and also increased the vegetation index in 2009 and 2010.
Completion of the superstructure stage of house constructions that provided suitable
environment for mosquitoes to breed in many locations, especially in the eastern part of
Jeddah, was the main reason for the shift of some districts from the highest and high risk
levels of female Aedes mosquitoes in 2009 to moderate risk level in 2010. Also, because
the majority of infected people in Al Balad, Al Hendaweyyah, Guleel, Al Thaalbah, Al
Kandarah and Betrumen, or where the highest and high risk levels of dengue fever cases
were observed in 2009 and 2010, were non-Saudi, they had a low rate of income which
led them to live in districts that have low rates of rent and contain labourers’ camps. These
districts have been determined to have had a low number of mosquitoes in 2009 and 2010.
All these facts confirmed that the victims of dengue fever during that period in those districts
were living in districts with a high or the highest risk level of mosquitoes and were getting
infected there. But when they went to hospital after the symptoms of the disease appeared,
they reported the names of the districts where they lived and not the names of the places
where they worked, hence causing a disjoint between high risk of Aedes mosquitoes and
reported DF infections.
Conclusion
Identifying dengue fever and its vector cluster and hot spots can be greatly enhanced through
the use of a variety of analytical techniques that are available in the Geographic Information
System (GIS). These techniques add considerable information to the disease investigations.
This study demonstrates that GIS spatial tools can be useful for dengue fever surveillance by
public health officials. It can provide an opportunity to specify the health burden of dengue
fever and its vector within the hot spots, and also sets a platform that can help to pursue
further investigations in associated factors that are responsible for an increased disease risk.
A concerted intervention in the districts of the high and the highest risk levels could be highly
31
effective in reducing dengue fever transmission in the study area as a whole. Getis-Ord
Gi‫ ٭‬and multi-distance spatial cluster (Ripley’s K-function) can be implemented as routine
procedures along with dengue fever control and prevention programmes. These spatial
techniques can be used on a weekly basis to identify and visualize the disease patterns and
hot spots as they develop. This information can then be used for treating, monitoring Aedes
mosquitoes and preventing DF prevalence. They can be used to check mosquito hot spots
as data are being collected and target these hot spot districts for spraying and eliminating
mosquito breeding sites, which is another key prevention measure. Construction sites,
labourers’ camps, swamps, soil depressions that retain water, block factories, animal fences,
fuel stations, cars and tyres repair shops, farms and storages should be under continuous
surveillance and treatment. Results from this study can be used to determine the order of
preference and for prioritizing control actions. Also, those areas where dengue fever cases
were detected but are not relatively well populated can be occasionally monitored for
mosquito density. Unfortunately, Jeddah districts have no spatial data of climatic factors that
can help us to build a model depending on dengue fever vector to illustrate to what extent
the spatial pattern of dengue fever cases in one year can be used to estimate the spatial
pattern for the coming year. We suggest that, in future, every trap that is used to capture
adult mosquitoes must have devices for measuring temperature, rainfall and relative humidity
to give a better understanding of the climatic conditions in the area. This can then be used
later to create temperature and rainfall surfaces for all of Jeddah districts and be used as
parameters for modelling predictable dengue incidences. In Saudi Arabia in general, and
in Jeddah in particular, highly mobile groups need an intensive educational programme on
dengue fever prevention and control. Dengue fever patients must report their travel history
to their doctors when travelling in epidemic areas to improve the quality of the surveillance
system.
Acknowledgements
We thank the Dengue Fever Operation Room of Jeddah Health Affairs and the Mosquito
Laboratory, Jeddah Municipality, for providing data on dengue fever infection cases and
female Aedes aegypti mosquito.
References
[1] Gubler DJ. Dengue and dengue hemorrhagic fever: its history and resurgence as a global public
health problem. In: Dengue and dengue hemorrhagic fever. Gubler DJ & Kuno G. eds. New York: CAB
International, 1997. p.1-22.
[2] Bergquist NR. Vector-borne parasitic diseases: new trends in data collection and risk assessment. Acta
Tropica. 2001, 79:13-20.
[3] Depradine CA, Lovell EH. Climatological variables and the incidence of Dengue fever in Barbados.
International Journal of Environmental Health Research. 2004; 14: 429-441.
32
[4] Wu PC, Lay JG, Guo HR, Lin CY, Lung SC, Su HJ. Higher temperature and urbanization affect the
spatial patterns of dengue fever transmission in subtropical Taiwan. Science of the Total Environment.
2009; 407: 2224-2233.
[5] Zaki A, Perera D, Jahan SS, Cardosa MJ. Phylogeny of dengue viruses circulating in Jeddah, Saudi
Arabia: 1994 to 2006. Tropical Medicine & International Health. 2008; 13: 584-592.
[6] Ibrahim NK, Abalkhail B, Rady M, Al-Bar H. An educational programme on dengue fever prevention
and control for females in Jeddah high schools. Eastern Mediterranean Health Journal. 2009; 15:
1058-1067.
[7] Siqueira JB, Maciel IJ, Barcellos C, Souza WV, Carvalho MS, Nascimento NE, Oliveira RM, Morais-Neto
O, Martelli CMT. Spatial point analysis based on dengue surveys at household level in central Brazil.
BMC Public Health. 2008; 8: 361.
[8] Ward MP. Spatio-temporal analysis of infectious disease outbreaks in veterinary medicine. clusters,
hotspots and foci. Vet Ital. 2007; 43: 559-570.
[9] Andrianasolo HH, Nakhapakorn K, Gonzalez JP. Remote sensing and GIS modelling applied to viral
disease in Nakhonpathom Province, Thailand. Igarss 2000: Ieee 2000 International Geoscience and
Remote Sensing Symposium, Vol I - VI, Proceedings 2000: 1996-1998.
[10] Aruna S, Nagpal BN, Joshi PL, Paliwal JC, Dash AP. Identification of malaria hot spots for focused
intervention in tribal state of India: a GIS based approach. International Journal of Health Geographics.
2009; 8: 30.
[11] Bousema T, Drakeley C, Gesase S, Hashim R, Magesa S, Mosha F, Otieno S, Carneiro I, Cox J, Msuya
E, et al. Identification of Hot Spots of Malaria Transmission for Targeted Malaria Control. Journal of
Infectious Diseases. 2010; 201: 1764-1774.
[12] Chaikaew N, Tripathi NK, Souris M. Exploring spatial patterns and hotspots of diarrhea in Chiang Mai,
Thailand. International Journal of Health Geographics. 2009; 8:36.
[13] Eisen L, Lozano-Fuentes S. Use of mapping and spatial and space-time modeling approaches in
operational control of Aedes aegypti and dengue. PLoS Negl Trop Dis. 2009; 3(4): e411.
[14] Hakre S, Masuoka P, Vanzie E, Roberts DR. Spatial correlations of mapped malaria rates with
environmental factors in Belize, Central America. International Journal of Health Geographics. 2004;
3(1): 6.
[15] Kitron U. Risk maps: Transmission and burden of vector borne diseases. Parasitology Today. 2000; 16:
324-325.
[16] Omumbo J, Ouma J, Rapuoda B, Craig MH, le Sueur D, Snow RW. Mapping malaria transmission
intensity using geographical information systems (GIS): an example from Kenya. Ann Trop Med Parasitol.
1998; 92: 7-21.
[17] Pratt M. Down-to-earth approach jumpstarts GIS for dengue outbreak. In: Book down-to-earth approach
Jumpstarts GIS for Dengue Outbreak (Editor ed.^eds.), Vol. 6(1). pp. 2. City: ESRI; 2003: 2.
[18] Ernst KC, Adoka SO, Kowuor DO, Wilson ML, John CC. Malaria hotspot areas in a highland Kenya
site are consistent in epidemic and non-epidemic years and are associated with ecological factors.
Malaria Journal. 2006; 5.
33
[19] Bautista CT, Chan AST, Ryan JR, Calampa C, Roper MH, Hightower AW, Magill AJ. Epidemiology and
spatial analysis of malaria in the Northern Peruvian Amazon. American Journal of Tropical Medicine
and Hygiene. 2006; 75:1216-1222.
[20] Achu DF. Application of GIS in temporal and spatial analyses of dengue fever outbreak: case of Rio de
Janeiro, Brazil. Master. Linköpings Universitet, Department of Computer and Information Science;
2008.
[21] Allen TR, Wong DW. Exploring GIS, spatial statistics and remote sensing for risk assessment of vectorborne diseases: a West Nile virus example. Int J Risk Assessment and Management. 2006; 6: 23.
[22] Bhandari K, Raju P, Sokhi B. Application of GIS modeling for dengue fever prone area based on socio
cultural and environmental factors – a case study of Delhi City Zone. The International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences. 2008: 6: 165-170.
[23] Aburas HM. ABURAS Index: A Statistically Developed Index for Dengue-Transmitting Vector Population
Prediction. Proceedings of World Academy of Science, Engineering and Technology. 2007; 23: 151154.
[24] Lagrotta MT, Silva WD, Souza-Santos R. Identification of key areas for Aedes aegypti control through
geoprocessing in Nova Iguacu, Rio de Janeiro state, Brazil. Cadernos De Saude Publica. 2008; 24:
70-80.
[25] Bailey TC, Gatrell AC. Interactive spatial data analysis. Harlow: Longman Scientific & Technical,
1995.
[26] Mitchell A. The ESRI Guide to GIS Analysis. ESRI Press. 2005, 2.
[27] Boots B, Getis A. Point pattern analysis. Sage University Paper Series on Quantitative Applications in
the Social Sciences, Series No. 07-001 Sage Publications 1988.
[28] Getis A, Ord JK. The Analysis of Spatial Association By Use Of Distance Statistics. Geographical Analysis.
1992; 24: 189-206.
[29] Nakaya T, Fotheringham AS, Brunsdon C, Charlton M. Geographically weighted Poisson regression for
disease association mapping. Statistics in Medicine. 2005, 24: 2695-2717.
[30] Honorio NA, Silva WdC, Leite PJ, Goncalves JM, Lounibos LP, Lourenco-de-Oliveira R. Dispersal of
Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in an urban endemic dengue area in the State
of Rio de Janeiro, Brazil. Memorias do Instituto Oswaldo Cruz. 2003; 98: 191-198.
34
Update on dengue in Africa
Fernando R.R. Teles#
Group of Mycology/Unit of Medical Microbiology and
Centre for Malaria and Tropical Diseases (CMDT),
Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL),
Rua da Junqueira, 100, 1349-008 Lisboa, Portugal.
Abstract
Dengue fever is a major public health problem worldwide, being considered one of the most
important re-emerging diseases of today. Dengue viruses and their mosquito vectors, while being
widely spread across all tropical and subtropical regions of the world, have recently emerged in
temperate regions as well. In Africa, both the virus and the vector mosquitoes exist, but, unlike in
Asia or South America, human dengue cases have been identified only occasionally, without reports
of severe outbreaks, until a few years ago. Recent episodes in the African continent evidenced
the lack of effective and reliable programmes for surveillance and control of dengue outbreaks.
This paper tries to give a brief overview of the current status of dengue in Africa and to assess the
main risk factors for any massive outbreaks in the future, while outlining the currently envisaged
strategies to face this emergent threat.
Keywords: Africa; Dengue virus; Aedes; Endemic; Vector control.
Introduction
Dengue disease is one of the most important arthropod-borne viruses of today. It affects
millions of people worldwide and is considered an emergent disease in both the developing
and developed worlds. Symptoms range from relatively mild dengue fever (DF) to the lifethreatening, severe haemorrhagic fever (DHF) or dengue shock syndrome (DSS). There are
four antigenically-related serotypes of DENV (DENV-1-4), all of them causing illness. WHO
reclassified ‘DHF’ as ‘severe dengue’ in an attempt to consider the frequent haemorrhagic
manifestations also observed in mild disease.[1] During the past millennium, dengue sylvatic
viruses were consistently and independently spread around the world, probably from southeast Asia, and introduced into human urban cycles. Dengue disease has been notified in
Africa since the early 20th century. Apart from the relatively few reported cases, outbreaks
#
35
in Africa have often been poorly documented, with no reliable data about the disease
incidence or prevalence. The scanty information sources available about dengue presence
and distribution in Africa include sporadic publications about local outbreaks, travellers’
infection cases and serosurveys, these being of very limited usefulness to determine the
true incidence and the epidemiological aspects of the disease in the continent. Human
population growth has been traditionally associated with increased dengue occurrences and
outbreaks; sustainable endemic transmission may require, at least, dozens of thousands of
people agglomerates,[2] thus occurring mainly among urban populations and in the presence
of domestic anthropophilic mosquitoes, able to transmit the infection among humans within
urban centres. Yet, even in urban African settings, severe DHF has been only occasionally
reported.[3]
Unlike in the Americas and Asia, the sylvatic transmission cycle of DENV seems to
predominate in West Africa. Despite the lack of systematic epidemiological and serosurveillance
data, several African countries have registered, over the past decades, significant increases
in the number of dengue epidemics, although at a much smaller scale than in south-east
Asia or in the Americas,[4] with few deaths and reduced morbidity. Vectorial capacity, host
genetics and virulence of viral strains have been implicated in this epidemiological pattern.
Ultimately, adequate dengue surveillance will be crucial to implement suitable vaccination
programmes, as expected for the near term.[5] This paper aims to assess the current status
of dengue disease in Africa and, from the epidemiological, entomological and genetic
perspectives, to evaluate the risk of the occurrence of severe dengue outbreaks as a major
public health problem in the continent.
The virus
Arbovirus infections presumably constitute a high proportion of undiagnosed febrile illnesses
in Africa. The existence of the disease, the prevalence of anti-dengue antibodies in the
scarcely reported serosurveys and their higher abundance with increasing age indicate
dengue endemicity in most regions of the continent.[5,6] The prevalence of dengue in Africa
seems to be lower than in Asia and in the Americas, but it is unclear if its emergence in the
last few years results more from real enhanced occurrence of the disease or from improved
reporting. The apparent low incidence and prevalence can still be ascribed to the increased
vulnerability of local populations to diseases as malaria, tuberculosis and AIDS (due to
socioeconomic and environmental determinants) than to dengue, or simply to the small
sample sizes usually tested in the few existing surveys.[5] Unlike the virus of yellow fever (YF),
which presents a well-known sylvatic transmission cycle, DENV evolved preferentially to a
human-to-mosquito-to-human urban cycle.[7] However, unlike in South America, sylvatic
cycles of DENV have been detected in West Africa and south-east Asia.[8] Here, forest vectormosquitoes are only moderately anthropophilic and a dominant sylvatic transmission cycle,
while occasionally affecting some humans, is most likely maintained by several Aedes spp.
mosquitoes and non-human primates.[9]
36
Nevertheless, the true role of non-human primate as hosts for DENV remains questionable,
as shown by a serological survey on Senegalese monkeys, where 100% of infected isolates
were tested negative for anti-dengue IgM and 58% positive for IgG, the latter probably due
to cross-reactivity with other flaviviruses.[10] The lack of reported human dengue outbreaks
caused by DENV sylvatic strains suggests that they are confined to the forests – given their
absence from pools of peridomestic mosquitoes from endemic dengue – or that they yield
relatively mild human disease.[11] The first genetic evidence of a sylvatic cycle probably arose
from a genome sequencing and profiling study of several isolates of DENV-1 and DENV-2
genotypes, where a single genotype (from DENV-2) represented an isolated forest virus
cycle that has evolved independently in West Africa.[12] In parallel, it is now known that
DENV urban strains infect sinantropic mosquitoes (e.g. Aedes aegypti and Aedes albopictus)
more easily than ancestral sylvatic DENV strains.[13] The existence of a permanent sylvatic
cycle constitutes an unlimited source of viral traffic to human hosts in urban environments,
making dengue eradication almost impossible. Experimental studies with different surrogate
human model hosts have shown no differences in the mean replication rates of sylvatic and
endemic DENV-2 strains, thereby suggesting that the presumable evolution of DENV sylvatic
into urban strains may not have required adaptation to replicate more efficiently in humans
than in ancestral animal hosts.[11] Thus, there is a considerable risk for dengue reintroduction
into the endemic urban cycle from the sylvatic circulation.
In fact, the first human case of DHF in Africa associated to a sylvatic DENV strain, of
DENV-2, was reported recently, in a patient from Guinea-Bissau returning to Spain. It is
possible that cases of sylvatic dengue have been underreported as clinical diagnosis, which
has largely constituted the predominant diagnostic approach for dengue in Africa, frequently
shows identical symptoms caused by endemic and sylvatic DENV strains.[14] Since DENV
is endemic in West Africa and DENV-2 is largely the predominant circulating serotype
(of endemic and sylvatic lineage as well), a secondary infection is unlikely to explain this
case’s disease severity. Unfortunately, serological diagnosis (mainly via the IgM/IgG ratio) is
inconclusive in distinguishing a secondary infection from a primary infection concomitant
with previous immunity to other flavivirus, strongly suggesting a primary infection with a
highly virulent sylvatic strain. Nevertheless, the potential of sylvatic strains as serious threats
to public health has been questioned.
Some authors focus on reports about dengue infections with similar severe symptoms
caused by endemic and sylvatic strains and on present DENV circulation in primates, despite
the ongoing deleterious human interventions in the tropical ecosystems[15] to support the
hypothesis about the risk for the emergence of human outbreaks caused by sylvatic dengue
viruses.[16] On the other hand, some writers claim that because of the only few number of
human dengue outbreaks reported in several decades that were caused by sylvatic DENV
strains, and the unlikelihood of the virus spillover from the sylvatic to the human cycle – in
accordance with the non-African origin of the strains that have caused human outbreaks in
the continent[17] – make such emergence unlikely to occur.[18] Meanwhile, the interpretation
37
about the significance and implications of clinical data, viraemia levels and human-driven
environmental disruption is not consensual.[16,18] Nevertheless, caution must be exercised
about the possible emergence of human dengue from sylvatic viral strains with enhanced
host and vector ranges.[17]
The vectors
The African-native Aedes aegypti mosquito species has been considered the main urbancycle dengue vector and the one responsible for all major DHF outbreaks.[19] This species
is composed by the subspecies Ae. aegypti aegypti and Ae. aegypti formosus. It is likely that
the ancestral sylvatic Ae. aegypti formosus from sub-Saharan forest became domesticated
by differentiating into the current Ae. aegypti aegyti urban subspecies. This original afrotropical mosquito then spread to other regions of the world, including the Mediterranean
and the Americas.[20] Ae. aegypti mosquitoes were involved in the late 2009 dengue outbreak
in Cape Verde islands.[21] Until a few decades ago, the physical isolation of the archipelago
could justify the absence of endemic vector-borne diseases, e.g. dengue or malaria.
However, the same factors that most likely explain the homogeneity of mosquito biodiversity
between the islands, especially urbanization and increased human, vector and pathogen
movements (apart differences in climate and vegetation), may favour, under appropriate
environmental conditions, the emergence of more frequent and severe outbreaks.[22] The role
of Aedes sp. mosquitoes other than Ae. aegypti in dengue transmission has been probably
underestimated due to the non-existence of reliable entomological and epidemiological
studies. Like Ae. aegypti, Ae. albopictus also infests urban environments,[23] thus acting as a
secondary vector of urban, epidemic dengue in Africa. This species has lower in vivo than
in vitro vectorial capacity for human infections. Human dengue is, indeed, the only disease
known to be transmitted in nature in epidemic form by Ae. albopictus,[19] but this species
has also been considered a less efficient epidemic vector than Ae. aegypti as a result of
differences in host preferences.[5] However, as for Ae. aegypti, geographical variations influence
susceptibility to dengue infection in these mosquitoes.[24] The general higher susceptibility of
Ae. albopictus than of Ae. aegypti for dengue viruses, as suggested by experimental infection
studies,[25] indicates a superior degree of adaptation as a result of longer historical contact.[13]
Ae. albopictus is the main dengue vector in Asia, where Ae. aegypti (an efficient vector for
both DENV and yellow fever virus (YFV)) is also abundant but in competitive disadvantage
with Ae. albopictus. In Africa, the relatively low abundance of Ae. albopictus compared to
that of Ae. aegypti, as well as the high cross-immunity between dengue and YF (by which
recovering from one disease decreases susceptibility to the other), might fully explain the
coexistence of both diseases in Africa and the absence of YF from Asia (even before the
introduction of mandatory vaccination, in most countries, for incoming travellers), as recently
demonstrated by mathematical modelling.[26]
In Africa, Ae. albopictus was first detected in South Africa in 1989, and, shortly afterwards,
in West Africa.[25] The species has been implicated, for several decades, as the main or even sole
38
vector in several dengue outbreaks in Africa.[27] In recent years, West and Central Africa have
experienced human co-infections of dengue and chikungunya (the last having Ae. albopictus
as the main vector), simultaneously with the invasion of the continent by Ae. albopictus.[25,28]
Even more surprising is the fact that such episodes of dengue epidemics have also occurred
in regions previously occupied by Ae. aegypti, and phylogenetic analysis confirmed that this
happened with urban rather than sylvatic DENV strains.[29] This phenomenon is probably
related with the above-mentioned higher susceptibility of Ae. albopictus for the virus. Such
highly probable association between Ae. albopictus territorial infestation and the emergence
of human dengue transmission and disease has been recently confirmed in Europe, with the
introduction of DENV in 2010 in the Mediterranean, where Ae. albopictus circulates, and
the onset of autochthonous viral circulation thereafter.[14] Experimental assays showed that
isolate pools of African mosquito species, tested for both DENV and CHIKV, were positive for
both viruses in most of the isolates of Ae. albopictus and negative for many other species, e.g.
Ae. aegypti.[29] In addition, well-succeeded experimental infection of African Ae. albopictus
mosquitoes with sylvatic, but even more with urban/epidemic DENV strains, was achieved.[30]
Unlike Ae. aegypti, Ae. albopictus has higher tolerance for temperate winters, thus presenting
a high risk for dengue spreading to non-tropical regions.[31]
Given the strong evidences about the high compartmentalization of both sylvatic and
urban dengue cycles, and apart from the suggestions about an eventual relevant role of
Ae. aegypti[24] and Ae. albopictus[19] in this regard, Aedes furcifer is perhaps the strongest
link for DENV exchange between the two cycles in view of its susceptibility to dengue
viruses and presence in both environments.[30] Indeed, only sylvatic strains of DENV-2 have
been reported, in association with the forest mosquitoes Ae. luteocephalus, Ae. taylori and
Ae. furcifer.[10] In East Africa, since 1980, a high abundance of mosquito populations has
accompanied the temperature increase observed in the highlands. In fact, the expected
rise in DENV incidence and geographical expansion in the African continent, especially in
eastern and central Africa, has been predicted by recent mathematical modelling based on
premises and evidences about climate and ecological changes suitable for enhanced dengue
transmission.[32] Nevertheless, the real impact of climate conditions on dengue incidence
and prevalence remains unclear and controversial.
In Africa, given the concurrence of various favourable conditions (including those of
socioeconomic origin) for the rapid emergence of severe dengue disease outbreaks, it would
be particularly interesting and useful to carry out prospective and/or retrospective studies
about the presumable correlation between climate, urban infestation by vector mosquitoes
and human epidemics, as well as entomological studies to assess the eventual implication
of sylvatic DENV strains, in order to assess the influence and dimension of such factors
in human dengue transmission. In particular, updates on the geographical distribution of
mosquito populations, and comparative analysis of vector-virus interactions including the
predominant Ae. aegypti and Ae. albopictus species, could clarify more properly the exact
and relative role of each species, especially of the new-comer Ae. albopictus, in the current
dengue emergence in Africa.[28]
39
Dengue in Africa
The first documented epidemic of DENV in Africa refers to South Africa (1927),[33] being the
first isolate, of DENV-1, obtained from Nigeria (1964).[34] Other cases and/or outbreaks of
DENV-1 were detected in Comoros (1993),[35] Ivory Coast (1999),[36] Cameroon (2002),[37]
Madagascar (2006),[38] Burkina Faso[39] and Sudan (1985).[40] DENV-2 was apparently
introduced in the continent from Indian Ocean islands,[12] although only few epidemics or
case reports from sylvatic DENV-2 in West Africa have been documented.[41] This apparent
lack of outbreaks caused by DENV-2 and the predominance of this serotype in sylvatic cycle
transmission is in accordance with the evidence about the relative compartmentalization of
the urban-human and the sylvatic-monkey dengue cycles.[12] Other human cases of DENV-2
have been detected in Senegal (1974, 1980, 1986, 1991, 1999 and 2008),[4,9,39,42] Nigeria
(1964),[34] Côte d’Ivoire (1980 and 2008),[39,43] Burkina Faso (1980 and 1983),[44,45] Guinea
(1981),[9] Seychelles (1977),[27] Kenya (1982),[46] Sudan (1985),[40] Comoros (1993),[35] Djibouti
(1991)[47] and Mali (2008).[38] The recent isolation of DENV-3 in East and West Africa suggests
that the serotype is spreading in the continent.[48] Simultaneous outbreaks of DENV-2 and
CHIKV were also reported in West Africa in the last few years, namely in Gabon.[29] DENV-3
probably spread from the Indian sub-continent to Africa in the 1980’s and from there to
Latin America in the mid-1990s.[49]
DENV-3 was initially reported in the continent during an outbreak in Mozambique in
1984-85,[50] where several secondary infections were reported. Shortly afterwards, in 1993,
a mixed outbreak of DENV-2 and DENV-3 occurred in the US military troops stationed in
Somalia.[38] Prior to DENV-3, DENV-1 and DENV-2 were reported as being endemic in the
region, where dengue was identified as a dominant cause of fever.[51] In West Africa, apart
from the recent large outbreak in Cape Verde (2009), and its co-circulation with YF in
Ivory Coast (2008),[38] DENV-3 has been isolated only in European travellers returning from
Benin (2010),[52] Comoros, Zanzibar (2010),[53] Cameroon (2006) and Senegal (2007 and
2009).[39,54] Senegal, in particular, has reported an unusual frequency of dengue outbreaks,
but this may be biased by improved surveillance in this country compared to most of the
others. The DENV-3 outbreak in Cape Verde, the largest dengue outbreak ever registered in
West Africa, was most likely a consequence of the increased travel and trade that occurred
between the archipelago and neighbouring African countries and, as such, a serious sign
that the virus is still spreading in the continent.[39] DENV-3 was detected in early samples,
ruling out the hypothesis of an escalation of the pandemic influenza A (H1N1) virus, which
was also affecting Cape Verde at the time. After this outbreak, which caused a few deaths
by DHF out of around 20 000 reported cases of dengue disease, the Cape Verde Health
Ministry requested a multidisciplinary task force from WHO aimed to evaluate the risk of
introduction of YF in the country. As a consequence, a stepwise vaccination programme and
improved controls at the frontiers were implemented.
The circulation of DENV-4 was detected in Senegal in the 1980s[42] and remained poorly
documented since then, indicating a negligible occurrence and impact. In Africa, DENV-2
40
accounts for most of the epidemics, followed by DENV-1.[4,38] Although the correlation
between dengue serotypes and disease patterns is uncertain, DENV-2 and DENV-3 seem to
be the main contributors to disease severity and mortality worldwide.[55] Owing to the scarcity
of documented dengue outbreaks in Africa, the true burden of the disease in the continent
is difficult to estimate, and therefore the scarcity of DHF episodes is not easy to interpret.
Since dengue endemicity in sub-Saharan Africa seems to be increasingly evident, growing
urbanization remains as a high-risk factor for large outbreaks of dengue in the continent.
Although most of the African people still live in rural regions, the overall urban population
in the continent increased 3-fold in the last 50 years.[5] Cities provide many artificial, nonbiodegradable containers that accumulate the necessary water for intense breeding of
mosquito larvae.[17] Yet, a very recent study in Viet Nam showed that DENV transmission
may be more intense in rural than in urban regions owing to the existence, in rural areas, of
higher mosquito-man ratios[56] and higher proportions of horizontally- than vertically-aligned
human habitations, creating higher risk for efficient DENV transmission than in tall buildings
(which have higher overall rather than ground-floor human densities than horizontal settings).
[57]
Given that, in Africa, more than 70% of the human population still lives in rural regions,[58]
a risk for large outbreaks becomes obvious. Even so, despite the unfavourable vector-host
ratio for efficient dengue transmission in cities, the absolute number of cases is, most likely,
higher in cities than in rural areas.[56]
Despite all DENV serotypes have already been reported in the continent, the reasons
for the apparent absence of severe dengue disease in Africa remain unclear. The available
evidences suggest that this low severity of human disease is multi-factorial. Low virulence of
viral strains, low genetic susceptibility of native black persons, high cross-protection conferred
by other native flavivirus’ antibodies from previous infections or vaccinations (e.g. from YF)
and low vectorial capacity of endemic mosquito populations,[30] probably contribute to the
scarcity of severe cases. Recent evidences have suggested that African sylvatic strains of dengue
viruses are less virulent than those circulating in other parts of the world, thus explaining, at
least in part, the historical lack of severe forms of dengue disease in Africa.[59]
Regarding host genetics, distinct clinical patterns of hospitalization between black and
white people observed in the Caribbean, with almost nonexistence of DHF/DSS among
blacks even in DENV hyperendemic regions,[60] have suggested lower genetic predisposition
of blacks to dengue, especially to its severe forms. This has been attributed to the existence
of polymorphic genes, unequally distributed among different ethnic groups (as a result of
different selective pressures exerted on geographically-split human ancestors), regulating
disease severity and resistance to infection. The identification of human genes regulating
infection susceptibility may render powerful tools for the combat and management of
dengue disease.
Given the common historical origins of black people from both the Caribbean and
Africa, it has been assumed that a common genetic profile between the two black people
groups might be associated with the low incidence of severe dengue cases and fewer
41
outbreaks in both tropical regions.[60,61] Genetically-controlled factors also regulate unequal
predisposition to dengue infection among different Aedes mosquito populations.[62] Indeed,
African Ae. aegypti populations have shown lower vectorial capacity for both sylvatic and
urban dengue viruses than Asian and American populations.[24] Low vectorial capacity can
be circumvented by relevant factors such as high local vector density, mosquito population
longevity or anthropophilic behaviour. Adult mosquito survival rates and density, both crucial
parameters for arbovirus transmission, are affected by eco-climatic factors. Even in the current
context of low DHF/DSS incidence in Africa, the presumable low vector susceptibility in the
continent may result, in the long term, on selection for higher viraemia and, in turn, to more
frequent and severe disease.[10] With respect to immunological factors, an eventual low rate
of dengue infection in Africa may result from cross-protecting immunity from heterologous
antibodies from other endemic flaviviruses in Africa.[5] A similar hypothesis was already
described to explain the absence of YF in Asia.[8]
Dengue control and surveillance
There are several strategies already employed or under development for control of dengue
disease, especially towards the production of a vaccine and new tools for control of vector
mosquito populations. Since the occurrence of DHF/DSS may essentially depend on the wellknown antibody-dependent immune enhancement effect (by which circulating antibodies
from a primary infection confer lifelong protection against the infecting serotype but induce
greater susceptibility to other serotypes in secondary infections and eventual haemorrhagic
symptoms), vaccination not targeted at all four serotypes will likely enhance susceptibility to
severe disease.[63] If, however, as it has been more recently proposed, distinct DENV serotypes,
and probably genotypes as well, may exhibit different virulence and/or transmissibility – both
factors influencing proneness to severe and epidemic disease – then an efficient strategy
to fight dengue would be direct control of the more virulent strains through vaccination.
Assuming that the last condition predominates, a future dengue vaccine, in practice, should
be effective against the four serotypes, and its use in African populations would be expected
to eradicate one or more serotypes within the endemic regions. However, without vector
control, this would not avoid the introduction of zoonotic strains into the human urban
cycle,[64] given the multiple forest niches of the virus. Only sustained vaccination programmes
could prevent this scenario, assuming the development, with time, of a strong protective
cross-reactivity between dengue urban strains used for vaccines and the zoonotic ones.[31]
Given the known difficulties and limitations of the insecticide-treated nets for mosquitobite prevention and the complexity and expensiveness of mosquito genetic control (e.g. by
releasing, into the natural environment, sterile males or transgenic mosquitoes) for application
in low-income countries and settings, the implementation and/or reinforcement of classical
insecticide-based mosquito eradication programmes should be reinforced, together with
continuous surveillance and monitoring, in order to prevent and/or minimize the emergence
42
of insecticide resistance. Data about insecticide susceptibility are essential to implement
effective and long-lasting control measures, especially regarding the most common insecticides
used for mosquito control in Africa. Yet, particularly in Central and West Africa, such data
are not available for Ae. albopictus, in view of the recent introduction of this species in the
continent, and outdated for Ae. aegypti.[65] It is suspected that insecticides commonly used for
other insects may also trigger selective pressure and thus insecticide-resistance in Aedes spp.
As such, DDT treatments used 50 years ago to control malaria most likely caused a drastic
reduction of Ae. aegypti populations in several African countries.[66] Subsequent relaxation
of vector control programmes led to latter reoccupation by this species, and, by competing
colonization, by Ae. albopictus.[2,20] A similar effect was observed in the 1950s–1970s
campaign to eradicate YF, whose interruption provoked quick Ae. aegypti recolonization
and, shortly afterwards, to the worldwide emergence of dengue disease.[31]
One of the most efficient Ae. aegypti control methods relies on the elimination of the
most common peridomestic breeding sites. It has been shown that, even in regions with high
human host density and mosquito/man ratios, regular supply of tap water eliminates most of
the mosquito breeding sites, with drastic reduction of dengue transmission.[56] However, this
strategy implies not only existing infrastructures but also a continuous and usually difficult
engagement of local human populations. Concerning Ae. albopictus, and taking into account
its non-African origin, an insecticide-resistance background cannot be excluded,[65] an aspect
deserving careful assessment. Considerable resistance of this species to pyrethroids has
recently been demonstrated in Singapore, through detection of a knock-down resistance
gene (kdr) mutation in these mosquitoes.[67]
Apart from the most common mosquito-borne way of infection, dengue may also be
occasionally transmitted by transfusion of contaminated blood.[68] In many endemic areas,
particularly in Africa, there is no routine practice in blood centres for DENV screening in
blood donations.[69] The importance of blood transfusion in dengue transmission is likely to
increase due to the growing rates of infection among aged people which, unlike children,
are potential blood donors. Accordingly, screening tests for dengue in blood supplies are
becoming available. As more adults will understandably be deferred or denied as blood donors
due to confirmed or suspected infection, the availability of blood supplies may decrease.
The expected rise in the number of DHF/DSS cases due to secondary infections will increase
the need for non-contaminated blood. A serious issue when considering diagnosis and
surveillance of dengue viruses is the mandatory knowledge about the endemicity levels and
prevalence of malaria. Febrile illnesses are not routinely diagnosed in laboratory in Africa and
recent evidences suggest that malaria has been overestimated in the continent, with many
of the reported fever cases being misdiagnosed as malaria rather than correctly diagnosed as
other diseases.[70] Among travellers returning from sub-Saharan Africa, malaria is surprisingly
much more prevalent as a cause of illness than dengue.[71] However, in addition to a possible
high underestimation of the true dengue cases, the average overestimation rate of malaria
by clinical diagnosis in low-transmission regions of Africa reaches 61%.[72]
43
Since many dengue infections are present subclinically or as fever of unknown
origin, they may remain undiagnosed and thus treated presumptively as malaria or other
common endemic fevers.[4] Especially in the early acute disease, clinical symptoms may be
undistinguishable, thus delaying the correct diagnosis and prompt therapeutic actions, which
may be crucial to combat these life-threatening diseases. Plus, erroneous attribution of fever
to malaria may lead to unnecessary exposure to the collateral effects of antimalarial drugs
(including malaria resistance) and, in endemic populations, to prolonged and worsening
illness, resulting in low labour productivity and avoidable burdening of national health systems.
Moreover, the increasing expensiveness and hazardousness of antimalarial drugs make malaria
presumptive treatment less acceptable than in the past.[73] This clearly highlights the need
for simultaneous specific diagnosis for dengue and malaria in patients living in or returning
from regions where both infections are endemic, or during dengue outbreaks. Indeed, the
possibility of undertaking mixed dengue-malaria field studies on native populations has
been proposed.[5] Due to the lack of dengue warning systems in Africa, returned travellers
have served as important sentinels for possible ongoing or imminent outbreaks, and thus
a crucial complement to the scarce local information.[54] Although not being endemic in
Europe, dengue is the most common cause of fever in returning travellers.[74] As in North
America, the presence of Aedes sp. mosquitoes, in parallel with massive human travelling
and migration, put these continents at serious risk of severe outbreaks.
Most African countries have established systems for HIV and YF diagnosis and surveillance,
but lack those for specific, rapid and accurate diagnostic tests for dengue. Indeed, as with
other illnesses of short incubation periods and frequently mild and/or nonspecific symptoms,
dengue may be underrepresented in epidemiological surveys.[71] Although the tourist flow
between Africa and Europe is still low compared to that arising from more popular touristic
destinations in South-East Asia or South America,[75] a significant increase of imported cases
from Africa has occurred since the 1990s.[39] Even so, it has been claimed that Africa seems
underrated in relation to dengue, considering the ratio of dengue-affected returning travellers
in relation to the overall number of returning travellers from Africa to Europe.[5] Proper
and prompt management of these suspected patients is urgently required to avoid costly
and cumbersome biosafety measures since, very often, the presence of a BSL-4 pathogen
cannot be ruled out in advance.[54] The high tourist flow between certain parts of Africa and
Europe highlights the need for early alerts about viraemic travellers and for entomological
surveillance,[53] especially since Ae. albopictus mosquito populations have become established
in several European countries.[76] Since a significant proportion of travellers may get ill during
travel owing to the short incubation period of the disease, there is an increasing need for
reinforcement of surveillance mechanisms in endemic countries.
So far, limited resource allocation for surveillance and research of dengue in Africa has
resulted from the underrating of the disease extension and burden, but this may be about
to change as climatic and socioeconomic factors will continue to favour its dissemination
in the continent. Except for some noticed local outbreaks, the more frequent reports about
dengue among travellers returning from Africa than in natives, and the fact that only half of the
44
African countries, where travellers have acquired dengue, reported local disease transmission,
strongly suggest the underestimation of dengue in the continent and the urgent need for its
improved diagnosis and surveillance.[5] It is known that human travelling and trade have put
in close contact geographically-separated mosquito populations, thus homogenizing their
genetic differences. In this regard, regular monitoring of Aedes mosquitoes’ geographical
distribution, especially through the integration of early detection systems into national
disease control programmes, will be crucial to accurately and timely assess the risk of dengue
transmission.
The US Army has recently implemented a complex multidisciplinary surveillance
programme, in order to build a predictive model for prevention, control and urgent response
to disease outbreaks.[77] The programme, which integrates datasets from satellite remote
sensing and geospatial mapping of eco-climatic events, as well as clinical and laboratorial
data, for the identification of critical detection points to assess the risk of outbreaks (Figure),
has proved its efficacy with the Rift Valley fever and is being extended to other infectious
diseases, including dengue. Recently, another theoretical model applied to DHF cases in
Thailand successfully identified, for the first time, a repeating spatial-temporal incidence
wave in a human vector-borne disease,[78] probably related with the above-mentioned effect
of discrepant transmission rates between urban centres and rural areas (probably peaking
most often when crossing rural regions). By accounting for the complex interaction between
Figure: Scheme of the Predictive Surveillance Program from The Armed Forces Health
Surveillance Center, Division of Global Emerging Infections Surveillance and Response
System Operations (AFHSC-GEIS)[77]. Data sources fill and enrich the warning system
framework. After reaching pre-established critical values, each model component triggers
partial alerts that, upon inter-communication and coordination, yield reliable predictions
about disease outbreaks aimed to produce prompt responses.
45
the eco-climatic factors that influence the pattern of DHF incidence, the model rendered
accurate predictions about the location and times of high incidence, allowing more efficient
allocation of resources to fight disease outbreaks. In conclusion, increased and improved
laboratorial diagnosis and surveillance are required to evaluate the epidemiological patterns
and public health burden of dengue in Africa.
Conclusion
Under a scenario of non-existence of effective drugs and vaccines, and given the well-known
difficulties in timely and accurately diagnosing the dengue disease, vector control for disease
prevention rather than responding to emergencies seems to be the best option available to
combat the illness, although more efficient insecticides and methods of application are also
needed. Unfortunately, the lack of infrastructure, health planning and economic affordability
in most African countries does not allow them to implement simple and effective means which
are available in richer tropical regions of the world, viz. window screening, air-conditioning
and simple hygienic practices. In the last few years, several institutions and initiatives have
been created to help WHO and governments fight dengue through new strategies and
tools for improved diagnosis, as well as to develop candidate drugs and vaccines. These
include the Paediatric Dengue Vaccine Initiative (PDVI), the Asia-Pacific Dengue Prevention
Partnership and the Consortium for the Study of Dengue Disease (DENFRAME). The European
Network for Imported Viral Disease-Collaborative Laboratory Response Network (ENIVDCLRN), the European Network on Imported Infectious Disease Surveillance (TropNetEurop)
and the Network of Medical Entomologists and Public Health Experts (VBORNET) of the
European Centre for Disease Prevention and Control (ECDC) are important assets to assist
the European Union (EU) and other countries in detecting, investigating and responding to
dengue outbreaks and even isolated cases, especially in returning travellers. In Africa, the
building of a sustainable research, diagnostic and surveillance capacity has been successfully
implemented through tight collaborations between WHO and the Pasteur Institute in Paris
for technology transfer to their African counterparts, namely, the Pasteur Institute in Dakar, a
WHO Collaborating Centre for arbovirus and viral haemorrhagic fevers, and a partner of the
Global Outbreak Alert and Response Network (GOARN), aimed at providing rapid response
to dengue and other arboviral outbreaks. This may certainly constitute a sustainable model
intervention to follow in the future.
Acknowledgements
The author most sincerely acknowledges the valuable contributions and helpful suggestions
made by Professor Aida Esteves and Professor Carla Sousa, from IHMT, which enabled him
to write this paper.
46
References
[1] Senanayake SN, Daveson KL. The Australasian Society for Infectious Diseases Annual Scientific Meeting
2010. Future Microbiology. 2010; 5: 1465-1467.
[2] Wang E, Ni H, Xu R, Barrett ADT, Watowich SJ, Gubler DJ, Weaver SC. Evolutionary relationships of
endemic/epidemic and sylvatic dengue viruses. Journal of Virology. 2000; 74: 3227-3234.
[3] Gubler DJ. The global emergence/resurgence of arboviral diseases as public health problems. Archives
of Medical Research. 2002; 33: 330-342.
[4] Sang R. Dengue in Africa. Working paper 3.3. In: Report of the Scientific Working Group on Dengue.
Geneva: WHO, 2006, 50-52.
[5] Amarasinghe A, Kuritsky JN, Letson GW, Margolis HS. Dengue virus infection in Africa. Emerging
[6] Fagbami AH, Monath TP, Fabiyi A. Dengue virus infections in Nigeria: a survey for antibodies in monkeys
and humans. Transactions of the Royal Society of Tropical Medicine and Hygiene. 1977; 71: 60-65.
[7] Barrett ADT, Higgs S. Yellow fever: a disease that has yet to be conquered. Annual Review of Entomology.
2007; 52: 209-229.
[8] Gubler DJ. The changing epidemiology of yellow fever and dengue, 1900 to 2003: full circle?
Comparative Immunology, Microbiology & Infectious Diseases. 2004; 27: 319-330.
[9] Vasilakis N, Holmes EC, Fokam EB, Faye O, Diallo M, Sall AA, Weaver SC. Evolutionary processes
among sylvatic dengue type 2 viruses. Journal of Virology. 2007; 81: 9591-9595.
[10] Diallo M, Ba Y, Sall AA, Diop OM, Ndione JA, Mondo M, Girault L, Mathiot C. Amplification of the
sylvatic cycle of dengue virus type 2, Senegal, 1999-2000: entomologic findings and epidemiologic
considerations. Emerging Infectious Diseases. 2003; 9: 362-367.
[11] Vasilakis N, Shell EJ, Fokam EB, Mason PW, Hanley KA, Estes DM, Weaver SC. Potential of ancestral
sylvatic dengue-2 viruses to re-emerge. Virology. 2007; 358: 402-412.
[12] Rico-Hesse R. Molecular evolution and distribution of dengue viruses type 1 and 2 in nature. Virology.
1990; 174: 479-493.
[13] Moncayo AC, Fernandez Z, Ortiz D, Diallo M, Sall A, Hartman S, Davis CT, Coffey L, Mathiot CC, Tesh
RB, Weaver SC. Dengue emergence and adaptation to peridomestic mosquitoes. Emerging Infectious
Diseases. 2004; 10: 1790-1796.
[14] Franco L, Placios G, Martinez JA, Vásquez A, Savji N, Ory F, Sanchez-Seco MP, Martin D, Ian Lipkin W,
Tenorio A. First report of sylvatic DENV-2-associated dengue hemorrhagic fever in West Africa. PLoS
Neglected Tropical Diseases. 2011; 5: e1251.
[15] Vasilakis N, Tesh RB, Weaver SC. Sylvatic dengue virus type 2 activity in humans, Nigeria, 1966.
Emerging Infectious Diseases. 2008; 14: 502-504.
[16] Vasilakis N, Cardosa J, Diallo M, Sall AA, Holmes EC, Hanley KA, Weaver SC. Sylvatic dengue viruses
share the pathogenic potential of urban/endemic dengue viruses. Journal of Virology. 2010; 84: 37263728.
47
[17] Monath TP. Dengue: the risk to developed and developing countries. Proceedings of the National
Academy of Sciences of USA. 1994; 91: 2395-2400.
[18] Mota J, Rico-Hesse R. Sylvatic dengue viruses share the pathogenic potential of urban/endemic dengue
viruses (author reply). Journal of Virology. 2010; 84: 3726-3728.
[19] Gubler DJ. Aedes albopictus in Africa. The Lancet. 2003; 3: 751-752.
[20] Failloux A-B, Vazeille M, Rodhain F. Geographic genetic variation in populations of the dengue virus
vector Aedes aegypti. Journal of Molecular Evolution. 2002; 55: 653-663.
[21] WHO. Dengue fever, Cape Verde. Weekly Epidemiological Record. 2009; 84: 469.
[22] Alves J, Gomes B, Rodrigues R, Silva J, Arez AP, Pinto J, Sousa CA. Mosquito fauna on the Cape Verde
Islands (West Africa): an update on species distribution and a new finding. Journal of Vector Ecology.
2010; 35: 307-312.
[23] Kamgang B, Happi JY, Boisier P, Njiokou F, Hervé J-P, Simard F, Paupy C. Geographic and ecological
distribution of the dengue and chikungunya virus vectors Aedes aegypti and Aedes albopictus in three
major Cameroonian towns. Medical and Veterinary Entomology. 2010; 24: 132-141.
[24] Diallo M, Ba Y, Faye O, Soumare ML, Dia I, Sall AA. Vector competence of Aedes aegypti populations
from Senegal for sylvatic and epidemic dengue 2 virus isolated in West Africa. Transactions of the Royal
Society of Tropical Medicine. 2008; 102: 493-498.
[25] Paupy C, Delatte H, Bagny L, Corbel V, Fontenille D. Aedes albopictus, an arbovirus vector: from the
darkness to the light. Microbes and Infection. 2009; 11: 1177-1185.
[26] Amaku M, Coutinho FAB, Massad E. Why dengue and yellow fever coexist in some areas of the world
and not in others? Biosystems. 2011; 106: 111-20.
[27] Matselaar D, Grainger CR, Oei KG, Reynolds DG, Pudney M, Leake CJ, Tukei PM, D’Offay RM, Simpson
DI. An outbreak of type 2 dengue fever in the Seychelles, probably transmitted by Aedes albopictus
(Skuse). Bulletin of the World Health Organization. 1980; 58: 937-943.
[28] Paupy C, Ollomo B, Kamgang B, Moutailler S, Rousset D, Demanou M, Hervé J-P, Leroy E, Simard F.
Comparative role of Aedes albopictus and Aedes aegypti in the emergence of dengue and chikungunya
in Central Africa. Vector-Borne and Zoonotic Diseases. 2009; 10: 259-266.
[29] Leroy EM, Nkoghe D, Ollomo B, Nze-Nkoghe C, Becquart P, Grard G, Pourrut X, Charrel R, Moureau
G, Ndjoyi-Mbiquino A, De-Lamballerie X. Concurrent chikungunya and dengue virus infections during
simultaneous outbreaks, Gabon, 2007. Emerging Infectious Diseases. 2009; 15: 591-593.
[30] Diallo M, Sall AA, Moncayo AC, Ba Y, Fernandez Z, Ortiz D, Coffey LL, Mathiot C, Tesh RB, Weaver
SC. Potential role of sylvatic and domestic African mosquito species in dengue emergence. American
Journal of Tropical Medicine and Hygiene. 2005; 73: 445-449.
[31] Weaver SC, Reisen WK. Present and future of arboviral threats. Antiviral Research. 2010; 85: 328345.
[32] Hales S, Wet N de, Maindonald J, Woodward A. Potential effect of population and climate changes on
global distribution of dengue fever: an empirical model. The Lancet. 2002; 360: 830-834.
[33] Kokernot RH, Smithburn KC, Weinbren MP. Neutralizing antibodies to arthropod-borne viruses in human
beings and animals in the Union of South Africa. Journal of Immunology. 1956; 77: 313-323.
48
[34] Carey DE, Causey OR, Reddy S, Cooke AR. Dengue viruses from febrile patients in Nigeria, 1964-68.
The Lancet. 1971; 1: 105-106.
[35] Boisier P, Morvan JM, Laventure S, Charrier N, Martin E, Ouledi A, Roux J. [Dengue 1 epidemic in the
Grand Comoro Island (Federal Islamic Republic of the Comoros). March-May 1993]. Annales de la
Société Belge de Médecine Tropicale. 1994; 74: 217-229.
[36] Durand JP, Vallee L, Pina JJ, Tolou H. Isolation of a dengue type 1 virus from a soldier in West Africa
(Côte d’Ivoire). Emerging Infectious Diseases. 2000; 6: 83-84.
[37] Krippner R, von Laer G. First confirmed dengue-1 fever cases reported from Cameroon. Journal of
Travel Medicine. 2002; 9: 273-274.
[38] WHO. Dengue in Africa: emergence of DENV-3, Côte d’Ivoire, 2008. Weekly Epidemiological Record.
2009; 84: 85-88.
[39] Franco L, Di Caro A, Carletti F, Vapalahti O, Renaudat C, Zeller H, Tenorio A. Recent expansion of
dengue virus serotype 3 in West Africa. Euro Surveillance. 2010; 15: pii=19490.
[40] Hyams KC, Oldfield EC, Scott RM, Bourgeois AL, Gardiner H, Pazzaglia G, Moussa M, Saleh AS, Dawi
OE, Daniell FD. Evaluation of febrile patients in Port Sudan, Sudan: isolation of dengue virus. American
Journal of Tropical Medicine and Hygiene. 1986; 35: 860-865.
[41] Monlun E, Zeller H, Traore-Lamizana M, Hervy JP, Adam F, Mondo M, Digoutte JP. Caractères cliniques
et épidémiologiques de la dengue 2 au Sénégal. Médecine et Maladies Infectieuses. 1992; 22: 718721.
[42] Saluzzo JF, Cornet M, Castagnet P, Rey C, Digoutte JP. Isolation of dengue 2 and dengue 4 viruses from
patients in Senegal. Transactions of the Royal Society of Tropical Medicine and Hygiene. 1986; 80: 5.
[43] Cordellier R, Bouchite B, Roche JC, Monteny N, Diaco B, Akoliba P. Circulation selvatique du virus
dengue 2 en 1980, dans les savanes soudaniennes de Côte d’Ivoire. Donnée entomologiques et
considérations épidémiologiques. Cahier ORSTOM Série Entomologie Médicale et Parasitologie. 1983;
21: 165-179.
[44] Robert V, Lhuillier M, Meunier D, Sarthou JL, Monteny N, Digoutte JP, Cornet M, Germain M, Cordellier
R. Virus amaril, Dengue 2 et autres arbovirus isolés de moustiques au Burkina Faso de 1983 à 1986:
considérations entomologiques et épidémiologiques. Bulletin de la Societé de Pathologie Exotique.
1993; 86: 90-100.
[45] Gonzalez JP, Du Saussay C, Gautun JC, McCormick JB, Mouchet J. [Dengue in Burkina Faso (ex-Upper
Volta): seasonal epidemics in the urban area of Ouagadougu]. Bulletin de la Société de Pathologie
Exotique et de ses Filiales. 1985; 78: 7-14.
[46] Johnson BK, Ocheng D, Gichogo A, Okiro M, Libondo D, Kinyanjui P, Tukei PM. Epidemic dengue
fever caused by dengue type 2 virus in Kenya: preliminary results of human virological and serological
studies. East African Medical Journal. 1982; 59: 781-784.
[47] Rodier GR, Gubler DJ, Cope SE, Cropp CB, Soliman AK, Polycarpe D, Abdourhaman MA, Parra JP,
Maslin J, Arthur RR. Epidemic dengue 2 in the city of Djibouti 1991-1992. Transactions of the Royal
Society of Tropical Medicine and Hygiene. 1996; 90: 237-240.
[48] Moi ML, Takasaki T, Kotaki A, Tajima S, Lim C-K, Sakamoto M, Iwagoe H, Kobayashi K, Kurane I.
Importation of dengue virus type 3 to Japan from Tanzania and Côte d’Ivoire. Emerging Infectious
Diseases. 2010; 16: 1770-1772.
49
[49] Messer WB, Gubler DJ, Harris E, Sivananthan K, Silva AM. Emergence and global spread of a dengue
serotype 3, subtype III virus. Emerging Infectious Diseases. 2003; 9: 800-809.
[50] Gubler DJ, Sather GE, Kuno G, Cabral JR. Dengue 3 virus transmission in Africa. American Journal of
Tropical Medicine and Hygiene. 1986; 35: 1280-1284.
[51] Tanaka M. Rapid identification of flavivirus using the polymerase chain reaction. Journal of Virological
Methods. 1993; 41: 311-322.
[52] Gautret P, Botelho-Nevers E, Charrel RN, Parola P. Dengue virus infections in travelers returning from
Benin to France, July-August 2010. Euro Surveillance. 2010; 15: ii=19657.
[53] Gautret P, Simon F, Askling HH, Bouchaud O, Leparc-Goffart I, Ninove L, Parola P, for EuroTravNet.
Dengue type 3 virus infections in European travelers returning from the Comoros and Zanzibar,
February-April 2010. Euro Surveillance. 2010; 15: pii=19541.
[54] Nísii C, Carletti F, Castilletti C, Bordi L, Meschi S, Selleri M, Chiappini R, Travaglini D, Antonini M,
Castorina S, Lauria FN, Narciso P, Gentile M, Martini L, Di Perri G, Audagnotto S, Biselli R, Lastilla M,
Di Caro A. A case of dengue type 3 virus infection imported from Africa to Italy, October 2009. Euro
Surveillance. 2010; 15: pii=19487.
[55] Guzman A, Istúriz RE. Update on the global spread of dengue. International Journal of Antimicrobial
Agents. 2010; 36S: S40-S42.
[56] Schmidt W-P, Suzuki M, Thiem VD, White RG, Tsuzuki A, Yoshida L-M, Yanai H, Haque U, Tho LH,
Anh DD, Ariyoshi K. Population density, water supply, and the risk of dengue fever in Vietnam: cohort
study and spatial analysis. PLoS Medicine. 2011; 8: e1001082.
[57] Barreto FR, Teixeira MG, Costa MC, Carvalho MS, Barreto ML. Spread pattern of the first dengue
epidemic in the city of Salvador, Brazil. BMC Public Health. 2008; 8: 51.
[58] Githeko AK, Lidsay SW, Confalonieri UE, Patz JA. Climate change and vector-borne diseases: a regional
analysis. Bulletin of the World Health Organization. 2000; 78: 1136-1147.
[59] Watts DM, Porter KR, Putvatana P, Vasquez B, Calampa C, Hayes CG, Halstead SB. Failure of secondary
infection with American genotype dengue 2 to cause dengue haemorrhagic fever. The Lancet. 1999;
354: 1431-1434.
[60] Halstead SB, Streit TG, Lafontant JG, Putvatana R, Russell K, Sun W, Kanesa-Thasan N, Hayes CG, Watts
DM. Haiti: absence of dengue hemorrhagic fever despite hyperendemic dengue virus transmission.
American Journal of Tropical Medicine and Hygiene. 2001; 65: 180-183.
[61] Sierra BC, Kourí G, Guzmán MG. Race: a risk factor for dengue hemorrhagic fever. Archives of Virology.
2007; 152: 533-542.
[62] Black WC IV, Bennett KE, Gorrochótegui-Escalante N, Barillas-Mury CV, Fernández-Salas I, Muñoz
ML, Farfán-Alé JA, Olson KE, Beaty BJ. Flavivirus susceptibility in Aedes aegypti. Archives of Medical
Research. 2002; 33: 379-388.
[63] Twiddy SS, Farrar JJ, Chau NV, Wills B, Gould EA, Gritsun T, Lloyd G, Holmes EC. Phylogenetic
relationships and differential selection pressures among genotypes of dengue-2 virus. Virology. 2002;
298: 63-72.
[64] Halstead SB. Dengue: overview and history. In: Halstead SB (ed.), Dengue. International Vaccine
Institute, South Korea, 2008, 1-28.
50
[65] Kamgang B, Marcombe S, Chandre F, Nchoutpouen E, Nwane P, Etang J, Corbel V, Paupy C. Insecticide
susceptibility of Aedes aegypti and Aedes albopictus in Central Africa. Parasites & Vectors. 2011; 4:
79.
[66] Ping LT, Yatiman R, Gek LP. Susceptibility of adult field strains of Aedes aegypti and Aedes albopictus in
Singapore to pirimiphos-methyl and permethrin. Journal of the American Mosquito Control Association.
2001; 17: 144-146.
[67] Kasai S, Ng LC, Lam-Phua SG, Tang CS, Itokawa K, Komagata O, Kobayashi M, Tomita T. First detection
of a putative gene in major mosquito vector, Aedes albopictus. Japanese Journal of Infectious Diseases.
2011; 64: 217-221.
[68] Tambyah PA, Koay ES, Poon ML, Lin RV, Ong BK; for the Transfusion-transmitted dengue infection
study group. Dengue hemorrhagic fever transmitted by blood transfusion. The New England Journal of
Medicine. 2008; 359: 1526-1527.
[69] Mohammed H, Linnen JM, Muñoz-Jordán JL, Tomashek K, Foster G, Broulik AS, Petersen L, Stramer
SL. Dengue virus in blood donations, Puerto Rico, 2005. Transfusion. 2008; 48: 1348-1354.
[70] Reyburn H, Mbatia R, Drakeley C, Carneiro I, Mwakasungula E, Mwerinde O, Saganda K, Shao J, Kitua
A, Olomi R, Greenwood BM, Whitty CJ. Overdiagnosis of malaria in patients with severe febrile illness
in Tanzania: a prospective study. BMJ. 2004 Nov 20; 329(7476): 1212.
[71] Freedman DO, Weld LH, Kozarsky PE, Fisk T, Robins R, von Sonnenburg F, Keystone JS, Pandey P,
Cetron MS. Spectrum of disease and relation to place of exposure among ill returned travelers. The
New England Journal of Medicine. 2006; 354: 119-130.
[72] Amexo M, Tolhorst R, Branish G, Bate I. Malaria misdiagnosis: effects on the poor and vulnerable. The
Lancet. 2004; 364: 1896-1898.
[73] Goodman CA, Coleman PG, Mills AJ. Changing the first line drug for malaria treatment. Health
Economics. 2001; 10: 731-749.
[74] Jelinek T, Muhlberger N, Harms G, Corachán MP, Grobusch MP, Knobloch J, Bronner U, Laferl H, Kapaun
A, Bisoffi Z, Clerinx J, Puente S, Fry G, Schulze M, Hellgren U, Gjørup I, Chalupa P, Hatz C, Matteelli
A, Schmid M, Nielsen LN, da Cunha S, Atouguia J, Myrvang B, Fleischer K. Epidemiology and clinical
features of imported dengue fever in Europe: sentinel surveillance data from TropNetEurop. Clinical
[75] Schwartz E, Weld LH, Wilder-Smith A, von Sonnenburg F, Keystone JS, Kain KC, Torresi J, Freedman
DO; GeoSentinel Surveillance Network. Seasonality, annual trends, and characteristics of dengue
among ill returned travelers. Emerging Infectious Diseases. 2008; 14: 1081-1088.
[76] Delaunay P, Jeannin C, Schaffner F, Marty P. Actualités sur la présence du moustique tigre Aedes
albopictus en France métropolitaine. Archives de Pédiatrie. 2009; 16: S66-S71.
[77] Witt CJ, Richards AL, Masuoka PM, Foley DH, Buczak AL, Musila LA, Richardson JH, ColaciccoMayhugh G, Rueda LM, Klein TA, Anyamba A, Small J, Pavlin JA, Fukuda MM, Gaydos J, Russell KL;
the AFHSC-GEIS Predictive Surveillance Writing Group. The AFHSC-Division of GEIS Operations
Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to
disease outbreaks. BMC Public Health. 2011; 11 (Suppl 2): S10.
[78] Cummings DAT, Irizarry RA, Huang NE, Endy TP, Nisalak A, Ungchusak K, Burke DS. Travelling waves
in the occurrence of dengue haemorrhagic fever in Thailand. Nature. 2004; 427: 344-347.
51
Involvement of the central nervous system in dengue
fever and its outcome
M.L. Kulkarni# & Saurabh Kumar
Department of Paediatrics, Jagadguru Jayadeva Muragharajendra (JJM) Medical College,
2373 MCC A Block, Davangere-577004, Karnataka, India.
Abstract
The involvement of the central nervous system in dengue-affected children, the spectrum of
neurological manifestations and the presence of dengue-specific IgM antibodies in the cerebrospinal
fluid (CSF) was studied. A prospective study was conducted of all consecutive serum-positive dengue
patients (n=100) admitted to the hospitals attached to the Jagadguru Jayadeva Murugharajendra
Medical College, Davangere, Karnataka state, India, from January 2009 to September 2010.
Children who presented with neurological symptoms were grouped separately and CSF was cultured
and routine tests for cells, sugar, protein and chlorides were done. Further CSF was subjected for
dengue IgM estimation.
The study showed that the neurological incidence was 40%. Seizures were present in 70% of cases
and altered sensorium was present in 80% of cases. Papilloedema and cranial nerve palsy were
observed in 30% of cases and meningeal signs were present in 80% of cases. CSF protein was high
in 80% of cases and pleocytosis was present in 80% of cases. CSF IgM was positive in 35% of cases.
The mortality observed in this study was 4%. It was concluded that dengue fever encompasses an
expanding clinical spectrum and is not just restricted to the WHO-specified criteria for making a
diagnosis of dengue fever other than dengue haemorrhagic fever and dengue shock syndrome. It
frequently causes encephalitis probably due to a direct neurotropic effect of dengue virus.
Keywords: Dengue fever; Encephalitis; Encephalopathy; Neurological manifestation of dengue fever.
Introduction
Dengue is the most rapidly-spreading mosquito-borne viral disease in the world. In the
last 50 years, its incidence has increased 30-fold with growing geographical expansion to
new countries, and, in the current decade, from urban to rural settings. Approximately 2.5
billion people live in dengue-endemic countries and an estimated 50–100 million dengue
infections occur annually.[1]
#
52
Involvement of the central nervous system in dengue fever and its outcome
Recent reports indicate that the clinical profile of dengue is changing. Neurological
manifestations are being reported frequently.[2,3] While the actual incidence of various
neurological complications is uncertain, the reported incidence of encephalopathy and
encephalitis, the most common neurological manifestations of dengue, have been found to
be between 0.5%–6.2%.[2,3]
From the pathogenesis point of view, neurological manifestations of dengue can be
grouped into three categories:
(1) Related to neurotropic effect of virus (encephalitis);
(2) Related to systemic complication of dengue infection (encephalopathy);
(3) Post infectious like acute disseminated encephalomyelitis, myelitis, Guillain-Barre
syndrome, optic neuritis.[4]
Since our hospitals are tertiary care hospitals, we do see a lot of children with dengue
infection, including those with neurological manifestations. So in this communication an
attempt has been made to know the neurological spectrum of dengue virus infection in
children and to estimate the IgM levels in the cerebrospinal fluid (CSF) of children with
neurological complications.
Materials and methods
This prospective study was conducted at the Chigateri General Government Hospital and the
Bapuji Child Health Institute, both tertiary care paediatric hospitals attached to the Jagadguru
Jayadeva Murugharajendra (JJM) Medical College, Davangere, Karnataka state, India, from
January 2009 to September 2010. In Davangere, the dengue epidemic occurred every year
from 2000 to 2006; since then it has become endemic with seasonal surge. A total of 100
children who were serologically positive for dengue were included in the study. The inclusion
criteria for this study was, all those children with fever and positive for serum IgM antibody for
dengue, and the exclusion criteria was, all those children with fever but negative for dengue
serology. In all 100 children, a detailed clinical history was taken, physical examination was
performed, and baseline investigations were done using a structured proforma. Tests were
done for haemoglobin (Hb), total and differential leukocyte count (TLC and TLC), platelet
count (PLT count), haematocrit (HCT) and liver function. All children were evaluated with
dengue serology using MAC ELISA method. CSF was subjected to dengue IgM estimation.
CSF analysis for IgM was done in children with neurological manifestations using Capture
ELISA method. The kit was brought from the National Institute of Virology, Pune, India.
The dilution for serum and cerebrospinal fluid was taken 1:100 and 1:10 respectively for
diagnostic significance as per the guidelines given by the institute. Pyogenic meningitis,
tubercular meningitis, hepatic encephalopathy and typhoid encephalopathy were excluded
by doing blood culture, Mantoux test, computed tomography scan, rapid malaria antigen
and optimal test, HBV serology and widal test. Herpes simplex serology and serology for
53
enterovirus were not done. CSF was cultured and routine tests for cells, sugar, protein and
chlorides were done. This study was purely observational.
The diagnosis of dengue infection, dengue fever and dengue haemorrhagic fever was
made according to the WHO criteria.[1]
Statistical analysis
Data were entered into a Microsoft Excel sheet. Frequencies, mean and standard deviation
were calculated by using Epi-info software for statistical analysis.
Ethical clearance was obtained from the Institutional Ethical Committee and the patients’
confidentiality regarding the data supplied was maintained.
Results
A total of 100 children (58 boys and 42
girls), who were serologically positive for
dengue antibody IgM, were part of the
study. Dengue fever was present in 42%,
dengue haemorrhagic fever in 32% and
dengue shock syndrome in 26% of cases.
Sixty children had no central nervous
system involvement. The most commom
symptom in this group was fever (100%),
followed by vomiting (50%), headache
(30%), abdominal pain (25%), arthralgia
(20%) and malena (10%). The most common
signs were hepatomegaly (78.3%), followed
by lymphadenopathy (55%), splenomegaly
(38.3%), petechiae and puffiness of eye
(30%) and rash (28.3%) (Table 1). In another
group who had neurological manifestations,
male:female ratio was 1.7:1. The clinical
spectrum of cases in which neurological
involvement (40 cases) was included,
constituted dengue fever (17 cases), DHF (13
cases) and DSS (10 cases). The most common
symptom in children who had neurological
manifestations was fever (100%), followed by
altered sensorium (82.5%), seizures (77.5%),
vomiting (57.5%) and headache (52.5%). The
54
Table 1: Signs and symptoms in children
without neurological manifestations,
Karnataka, India
Clinical features
Fever
Children without
neurological
manifestations
(n=60)
(%)
60 (100)
Vomiting
30 (50)
Headache
18 (30)
Abdominal pain
15 (25)
Arthralgia
12 (20)
Malena
6 (10)
Lymphadenopathy
33 (55)
Puffiness
18 (30)
Petechiae
18 (30)
Rash
17 (28)
Hepatomegaly
47 (78)
Splenomegaly
23 (38)
most common signs were meningeal signs
(80%), cranial nerve palsy and papilloedema
(32.5%). The most common cranial nerves
involved were 6th and 7th.
Hepatomegaly and splenomegaly
were present in 65% and 37% of cases
respectively. In children with neurological
manifestation, oedema was present in 37%
of cases and rash and petechiae were seen
in 25%. Malena was found only in one case
(Table 2). Thrombocytopenia was present
in 47.5% in children with neurological
manifestations. SGOT (serum glutamic
oxaloacetate transaminase) and SGPT
(serum glutamic pyruvate transaminase)
showed significant elevation in children with
neurological manifestations when compared
to those without neurological manifestations
(P value <0.005 and <0.040 respectively).
CSF analysis was done in all 40 cases who
had neurological manifestations; protein was
in the range of 28–178 mg/dl, with a mean
of 84.6 mg/dl. Glucose was in the range of
4–86 mg/dl with a mean of 47.67 mg/dl. Cell
count was in the range of 4–360 mm3 with a
mean of 61.09 mm3. CSF IgM was positive
in 14 cases out of 40 cases, in which 6 cases
were of simple dengue fever, 4 of DHF and
another 4 of DSS (Table 3). Clinical features
of CSF IgM-positive cases are mentioned in
Table 4. Computed tomography was done in
5 patients. It was normal in 4 cases and in 1
case, it showed cerebral oedema.
Discussion
Dengue is one of the most important
arboviral infections of humans and is one
of the most important tropical infectious
diseases in the world. The occurrence of
Table 2: Signs and symptoms in children
with neurological manifestations,
Karnataka, India
Clinical features
Mean age in years
M/F ratio
Children with
neurological
manifestations
(n=40)
(%)
6.9
1.7:1
Fever
40 (100)
Fever at the time of
admission in days ±
SD
9.5±6.3
Altered sensorium
33 (82.5)
Seizure
31 (77.5)
Vomiting
23 (57.5)
Headache
21 (52.5)
Abdominal pain
7 (17.5)
Arthralgia
3 (7.5)
Malena
1 (2.5)
Lymphadenopathy
24 (60)
Puffiness
15 (37.5)
Petechiae
15 (37.5)
Hepatomegaly
26 (65)
Splenomegaly
15 (37.5)
Rash
10 (25)
Meningeal sign
32 (80)
CN palsy
13 (32.5)
Papilloedema
13 (32.5)
Mortality
3 (7.5)
55
Table 3: Laboratory investigations in children with neurological manifestations,
Karnataka, India
Investigations
Mean Hb (gm%) ± SD
Mean total leukocyte count (per mm3) ± SD
(4–11x103/µL)
Children with neurological
manifestations (n=40)(%)
P value
9.7±1.9
NS
8785±6233
Platelet count (per mm3) in blood
(150–500x103/µL)
<30 000
4 (7.5)
31 000–50 000
3 (10)
51 000–100 000
12 (30)
>100 000
21 (52.5)
Mean packed cell volume (PCV) (%) ± SD
28.5±5.3
<0.042 S
Mean SGOT (IU) SD (SGOT 5–35 U/L)
388±236
<0.005 S
Mean SGPT (IU) SD (SGPT 7–56 U/L)
301±266
<0.040 S
CSF findings (40 patients)
CSF pleocytosis (>10 cells/mm3)
80
Mean cell count ± SD (WBC 0-3/µL)
61.09±63.56
Mean CSF protein ± SD (15–45 mg/dL)
84.6±45.56
Mean CSF sugar ± SD ( 50–80 mg/dL)
47.6±19.9
CSF IgM positivity
14 (40)
DF
6
DHF
4
DSS
4
neurological manifestations in dengue infection has been recognized for long.[3] In previous
reports of neurological involvement in dengue infection, the observed ‘encephalopathy’
was thought to be due to prolonged shock, along with fluid extravasation, cerebral oedema,
hyponatremia and liver failure.[5] Recently, however, direct neurotropic potential of the
virus has been recognized.[6] In India, too, neurological complications of dengue have been
reported.[7]
56
Out of our 100 cases, 40 children
had symptoms and signs pertaining to
CNS involvement. Hence, the incidence
of neurological involvement in our study
was 40%, which we believe is very high
as compared to other studies. [2,3] The
neurological manifestation was 0.5% and
6.2% in the study done by Cam et al.[2]
and Hendarto et al.[2,3] respectively. The
incidence of neurological involvement was
more in the children who met the clinical
features of the WHO-specified criteria of
only dengue fever. Similar observations
were made by Misra et al.[8] who suggested
that neurological involvement may not be
necessarily due to shock or bleeding. It may
be due to direct neurotropic effect of the
virus. In the present study, however, altered
sensorium and convulsions were the most
frequent presentations, which was almost
similar to previous observations made by
Solomon et al.[5]
Table 4: Clinical features of CSF IgM
positive patients, Karnataka, India
Clinical features
Children with
neurological
manifestations
(n=14)
(%)
Fever
14 (100)
Altered sensorium
13 (92.5)
Seizure
12 (85.5)
Vomiting
9 (64.2)
Headache
9 (64.2)
Abdominal pain
4 (28.5)
Lymphadenopathy
6 (42)
Puffiness
5 (35.5)
Petechiae
4 (28.5)
Hepatomegaly
10 (71)
Splenomegaly
6 (42)
An interesting observation we made
in our case study was that the presence
Rash
5 (35.5)
of papilloedema and meningeal signs was
Meningeal sign
12 (85.5)
significantly more, being 32.5% and 80%
respectively. CSF pleocytosis is an indication
CN palsy
12 (85.5)
of the inflammation of meninges and
Papilloedema
7 (50)
encephalon, probably due to direct viral
invasion. In our study, CSF pleocytosis was
seen in 82% of the cases. Though the gold
standard for diagnosing viral encephalitis is isolation of virus either from neural tissue or
CSF, however, detection of viral-specific IgM in the CSF is considered as an indication of
viral replication in the CNS. In the present study, CSF IgM was positive in 40% of the cases,
which is a little less when compared to the other studies. CSF IgM was positive in 47% and
64% in the studies done by Soares et al.[9] and Cam et al.[2] In the group of patients which
had neurological manifestations, the mortality rate was 7.5% and there was no morbidity.
All the other patients recovered without any neurological deficit.
57
Conclusion
Dengue is a major public health problem in Davangere and surrounding districts in the state
of Karnataka in south India. A wide range of neurological manifestations were observed in
our study. Altered sensorium, seizures, papilloedema, cranial nerve palsy and meningeal
signs were among the common manifestations. Detection of dengue-specific IgM in CSF
using ELISA has high specificity and it is difficult to explain the presence of IgM antibody
in the CSF other than by viral invasion across the blood brain barrier. In our study, IgM in
CSF was isolated in 14 (40%) cases, along with mean CSF protein of 84 mg/dl and with CSF
mean cell count of 61 cells/mm3, which suggest viral invasion into the CNS. In an endemic
area, dengue encephalitis should be considered in patients who present with the clinical
features of encephalitis, whether or not classical manifestations of dengue are present or not.
Standard case definition for dengue encephalitis, if adopted by WHO, would help clarify
the importance of dengue neurotropism worldwide.
References
[1] World Health Organization. Dengue: guidelines of diagnosis, treatment, prevention and control. New
edition. Geneva: WHO, 2009.
[2] Cam BV, Fonsmark L, Hue NB, Phoung NT, Poulsen A, Heegaard ED. Prospective case control study of
encephalopathy in children with dengue hemorrhagic fever. Am J Trop Med Hyg. 2001; 65: 848-51.
[3] Hendarto SK, Hadinegoro SR .Dengue encephalopathy. Acta Peadiatr. Jpn. 1992; 34: 350-7.
[4] Murthy JMK. Neurological complication of dengue infection. Neurol India. 2010; 58: 581-84.
[5] Solomon T, Dung NM, Vaughn DW, Kneen R, Thao LT, Raengsakulrach, et al. Neurological manifestations
of dengue infection. Lancet. 2000; 355:1053-9.
[6] Lum LC, Lam SK, Choy YS et al. Dengue encephalitis: a true entity? Am J Trop Med Hyg. 1996; 54:
256-9.
[7] Rajajee S, Mukundan D. Neurological manifestation of dengue hemorrhagic fever. Indian Pediatr.
1994; 31: 688-9.
[8] Misra UK, Kalita J, Syam UK, Dhole TN. Neurological Manifestation of dengue viral infection. J Neurol
Sci. 2006; 244(1-2): 117-22.
[9] Soares CN, Faria L.C, Peralta J.M, Freitas M.R.G, Puccioni-sohler M. Dengue infection: neurological
manifestation and cerebralspinal fluid analysis. Journal of the Neurological Science. 2006; 249: 1924.
58
Clinical and biochemical characteristics of suspected
dengue fever in an ambulatory care family medical
clinic, Aga Khan University, Karachi, Pakistan
Firdous Jahan,# Kashmira Nanji, Waris Qidwai, Rozina Roshan & Hira Waseem
Department of Family Medicine (FAMCO), Oman Medical College-Sohar, PO Box 391,
PC 321 , Al-Tareef, Sohar, Sultanate Oman.
Abstract
A medical chart review was carried out in an ambulatory family medical clinic attached to the
Aga Khan University Hospital, Karachi, Pakistan. The study revealed that all febrile patients the
mean fever spike was 39.8°C. The common symptoms were bodyache (46%), nausea (12%) and
headache (10%). Other clinical findings were eye pain, backache and anorexia. Out of thirteen
patients who had dengue IgM done, nine showed positive results. In laboratory examination,
thrombocytopenia was found in 53.4% of patients. Low haemoglobin was found in 51% and
leucopenia in 32.9% of patients.
Keywords: Dengue fever; Ambulatory care; Medical chart review; Clinical and biochemical changes; Suspected
DF; Aga Khan University Hospital; Karachi, Pakistan.
Introduction
Dengue is a widespread mosquito-borne infection in human beings which, in recent years,
has become a major public health concern worldwide.[1] Dengue is re-emerging throughout
the tropical world, causing frequent recurrent epidemics.[2,3] In Pakistan, the first major
outbreak was recorded in 1994 in Karachi. Since then, Karachi has experienced recurrent
outbreaks during 2005, 2006 and 2010. Other cities in Pakistan which recorded major
dengue outbreaks were Lahore (2008) and Islamabad (2010). Three serotypes, viz. DENV-1,
DENV-2 and DENV-3 (subtype III), have been found circulating in the country.[4]
During 2010, the Dengue Surveillance Cell of the Sind Province of Pakistan reported 563
serologically-confirmed cases at the Aga Khan University Hospital in Karachi. The reported
cases were usually complicated or were with haemorrhagic manifestations. However, at an
#
59
Clinical and biochemical characteristics of dengue fever cases in Karachi, Pakistan
ambulatory care family medical clinic (primary health care centre) attached to the Aga Khan
University Hospital, the usual presentation was mild-to-moderate fever, treated as suspected
dengue. The present study highlights the clinical and biochemical characteristics of suspected
cases as observed at an ambulatory care family medical clinic (ACFMC).
The primary investigator of this study trained the person who did the chart review and data
collection in the clinic. Data were collected through a structured instrument which was
developed after brainstorming sessions with the authors.
Demographic information, gender and age were recorded for all patients. Clinical
presentation (fever), minimum and maximum rise of temperature, nausea and/or vomiting,
rash, abdominal pain, myalgia, headache and haemorrhage were recorded. Results of
biochemical tests, which were carried out depending on clinical findings, were recorded.
Thrombocytopenia was defined as a platelet count, 100 000 cells/mm3 blood. A
haematocrit value rising by 20% was considered as high. Similarly, leucopenia was defined as
a white cell count <5000 cells/mm3, neutropenia as neutrophils <40%, and lymphocytosis
as lymphocytes >45%. Alanine aminotransferase (ALT) was considered as raised if it was
55 and 33 IU/L for males and females respectively. Aspartate aminotransferase (AST) was
defined as raised if it was 46 and 32 IU/L for males and females respectively.
The Statistical Package for Social Sciences (SPSS) version 15.0 was used for data entry and
statistical analysis. Descriptive statistics were calculated. Median (± inter-quartile ranges) were
reported for continuous variables such as age, gender, etc. Numbers and percentages were
reported for all other categorical variables such as clinical characteristics (fever, headache,
bodyache, etc.) and biochemical tests (thrombocytopenia, leucopenia, etc.)
Most developing countries have epidemics of febrile illnesses which can be confused
with dengue fever; therefore, other investigations such as blood culture, urine culture,
malaria immunochromatography (ICT), typhidot IgM, etc., were done according to clinical
symptoms and signs.
Results
The total number of patients who presented with fever in the community health centre
(outpatient clinic) during October-November was 125, of whom 78 (62.4%) were male
while 47 (37.6%) were female.
60
The mean fever spike was 39.8 °C. The common symptoms were bodyache (46%),
nausea (12%) and headache (10%). Other clinical findings were eye pain, backache and
anorexia (Table 1).
Table 1: Clinical features of patients with suspected DF at an ambulatory care family
medical clinic, Karachi, Pakistan
Characteristics
n
Age*
%
32 (±15)
Gender
Male
78
62.4
Female
47
37.6
Bodyache/headache
69
55
Eye pain
4
3.2
Backache
41
32.8
Nausea/Anorexia
11
8.8
*Mean age.
In laboratory investigations, thrombocytopenia was found in 50 out of 92 (54.3%)
patients. Low haemoglobin was found in 44 out of 86 (51%) patients, high haemoglobin
and haematocrit level was found in 42 out of 86 (48%) patients, leucopenia in 29 out of 89
(32.9%), neutropenia in 9 out of 70 (13%), lymphocytosis 10 out of 69 (14.5%), lymphopenia
26 out of 69 (37.6%), raised ALT 17 out of 41 (41%) and raised AST 25 out of 29 (86%)
patients. Raised ALT/AST was found in 5% of the cases (Table 2). Dengue IgM was done
in 13 patients and 9 were positive (69.2%). Other investigations done according to clinical
presentation revealed significant positive blood culture for Salmonella Typhi and serum
Typhidot-IgM.
Severe thrombocytopenia <30 000 was found in 9 (7%) cases, high haematocrit >20
was found in 84 (67%) cases and severe leucopenia <3.0 was found in 12 (10%) cases. Based
on these criteria, 52 patients were referred to the Emergency and 9 were hospitalized for
platelet transfusion; the rest were sent home after intravenous rehydration and were asked
to return for a close follow-up in the ACFMC clinic.
61
Table 2: Laboratory findings of the study participants with suspected DF (n=125)
Tests
n=Tests ordered
Test positive
%
Thrombocytopenia
92
50
54.3
Low haemoglobin
86
44
51
High haemoglobin
86
42
48
Haematocrit level
70
Lymphocytosis
69
10
14.5
Leucopenia
89
29
32.5
Neutropenia
70
9
13
Raised AST
29
25
86
Raised ALT
41
17
41
40±5.8
Discussion
The results of this study describe the demographic trends of suspected dengue infections in
ambulatory care. As described in available literature, the clinical presentation is somehow
classical in most of the suspected DF cases.[5] Dengue virus is now endemic in Pakistan,
circulating throughout the year, with a peak incidence in the post-monsoon period. The
mean age detected is 32 years (3-78). The median age of dengue patients has decreased
and younger patients seem to have become more susceptible.[6]
Clinical presentation in nearly half of the patients was severe bodyache followed by
backache, nausea and headache as reported by others.[7] In those who had the diagnosis of
suspected DF, the most common biochemical changes were thrombocytopenia and raised
AST. Nearly half of the patients had high haemoglobin and haematocrit levels. Dengue IgM
was positive in 9 out of 13 patients on whom the test was done. Among patients of DF in
other parts of Pakistan, tests revealed similar clinical characteristics, with some variations in
symptomatology.[8,9].
Clinical characteristics and biochemical changes, though variable in different parts of
the world, show some similarities like thrombocytopenia, high haematocrit, leucopenia,
lymhocytosis and lymphonia, that were found in this audit as well.[5,10,11,12] Both ALT and
AST levels were high in the biochemical profile but the level of AST was significantly high.[13]
Total and differential leukocyte count may be useful for the identification of patients at risk
of haemorrhage and their utility needs should be studied further.
62
Other diagnosis in ambulatory care was enteric fever in 34 out of 53 (62%) patients.
Although malaria is highly prevalent in this part of the country, but in post-monsoon fever
cases, out of 59 tests done, only one malaria ICT was found positive. A significant number
of patients were referred to the Emergency room for hospitalization, but most of them
were discharged after intravenous rehydration while 9 out of 52 patients needed platelet
transfusion. In this study no one had overt bleeding or minor haemorrhage but cases of
impending haemorrhage with severe thrombocytopenia were immediately referred for
platelet transfusion. Primary care physicians have an active role to play in providing care and
support and identifying the signs of impending haemorrhage which has serious consequences.
Dengue fever cases need referral to tertiary care for intravenous fluid replacement and
platelet transfusion along with supportive care.
Acknowledgements
The authors gratefully acknowledge the help of Sumiara Ihtesham (Head Nurse, CHC Clinic)
and Dr Samina Hossien (Assistant Physician In-charge, CHC Clinic).
References
[1] World Health Organization. Dengue and dengue haemorrhagic fever. Fact sheet no.117 March 2009.
Geneva: WHO, 2009. - http://www.who.int/mediacentre/factsheets/fs117/en/ - accessed 11 January
2012.
[2] Guzman MG, Kouri G. Dengue: an update Lancet Infect Dis. 2002; 2: 33–42.
[3] Thomas SJ, Strickman D, Vaughn DW. Dengue epidemiology: virus epidemiology, ecology, and
emergence. Adv Virus Res. 2003; 61: 235–289.
[4] Raheel U, Faheem M, Riaz MN, Kanwal N, Javed F, Zaidi NS, Qadri I. Dengue fever in the Indian
subcontinent: an overview. J Infect Dev Ctries. 2011; 26; 5(4): 239-47.
[5] Ageep AK, Malik AA, Elkarsani MS. Clinical presentations and laboratory findings in suspected cases
of dengue virus. Saudi Med J. 2006 Nov; 27(11):1711-3.
[6] Syed M, Saleem T, Syeda UR, Habib M, Zahid R, Bashir A, Rabbani M, Khalid M, Iqbal A, Rao EZ,
Shujja-ur-Rehman , Saleem S. Knowledge, attitudes and practices regarding dengue fever among adults
of high and low socioeconomic groups. J Pak Med Assoc. 2010 Mar; 60(3): 243-7.
[7] Muhammad A, Adel MK, Eman HL, Shahid B, Adnaan YA, Sawsan AU. Characteristics of Dengue Fever
in a large public hospital, Jeddah, Saudi Arabia. J Ayub Med Coll Abottabad. 2006 Jun; 18(2): 9-13.
[8] Riaz MM, Mumtaz K, Khan MS, Patel J, Tariq M, Hilal H, Siddiqui SA, Shezad F. Outbreak of dengue
fever in Karachi 2006: a clinical perspective. J Pak Med Assoc. Jun 2009; 59(6): 339-44.
[9] Khan E, Siddiqui J, Shakoor S, Mehraj V, Jamil B. Dengue outbreak in Karachi, Pakistan, 2006: experience
at a tertiary care center. Trans R Soc Trop Med Hyg. 2007; 101: 1114–1119.
63
[10] Keating J. An investigation into the cyclical incidence of dengue fever. Soc Sci Med. 2001; 53:
1587–1597.
[11] Gupta E, Dar L, Kapoor G, Broor S. The changing epidemiology of dengue in Delhi, India. Virol J.
2006; 3: 92.
[12] Chuang VW, Wong TY, Leung YH, Ma ES, Law YL. Review of dengue fever cases in Hong Kong during
1998 to 2005. Hong Kong Med J. 2008; 14: 170–177.
[13] Sumarmo. Dengue haemorrhagic fever in Indonesia. Southeast Asian J Trop Med Public Health. 1987;
18: 269–274.
64
Capillary leak syndrome in dengue fever
Sudhir Kumar Verma,a Manish Gutch,a Abhishek Agarwalb & A.K. Vaisha#
Department of Medicine, Chhatrapati Shahuji Maharaj Medical University (CSMMU),
Chowk, Lucknow-226003, Uttar Pradesh, India.
a
Department of Pulmonary Medicine, Chhatrapati Shahuji Maharaj Medical University (CSMMU),
Chowk, Lucknow-226003, Uttar Pradesh, India.
b
Abstract
Capillary leak syndrome (CLS) has been described in dengue fever but its exact features have not
been clearly defined. We present here the findings in 25 cases of CLS recently seen by us during an
outbreak of dengue fever in northern India. Besides fever, body ache and bleeding manifestations,
ascites was present in 84% cases, pleural effusion in 76% cases, and both ascites and pleural
effusion in 60% of cases. The pleural effusion was right-sided in 52.6% cases, bilateral in 47.4%
cases and only left-sided in none of the cases. The fluid accumulation seen was moderate and
frequently involved both abdomen and pleural cavity. The fluid rapidly cleared in a week’s time
without any specific treatment. These cases can pose considerable diagnostic challenge which is
discussed here.
Keywords: Dengue fever; Pleural effusion; Ascites; Capillary leak syndrome.
Introduction
Capillary leak syndrome (CLS) can be due to diverse causes.[1] There are several reports of
CLS in dengue fever but its precise manifestations have not been clearly defined.[2,3] Recently,
in an outbreak of dengue fever in northern India, we encountered several cases of CLS. The
detailed findings of CLS in these cases are being presented here.
Out of the 127 cases seen in one month at the Chhatrapati Shahuji Maharaj Medical University
(Erstwhile King George Medical College), Chowk, Lucknow, Uttar Pradesh, India, 25 cases
had features of CLS. All the cases of dengue fever with CLS were positive for NS1 antigen
(Dengue NS1 Antigen Microlisa Kit marketed by J. Mitra & Co., India) or IgM antibodies (IVD
IgM dengue kit marketed by IVD Research Inc., USA) or both (Table 1).
#
65
Table 1: Results of testing for dengue fever
(NS1 & IgM antibody)
Test
Positive (%)
(n=25)
NS1 antigen
4 (16%)
IgM dengue antibody
17 (68%)
Both
4 (16%)
The other investigations performed
in these cases were complete haemogram
including platelet count, urine routine
examination, blood urea nitrogen,
blood sugar, total serum protein &
serum albumin, ultrasonographic
examination of abdomen and X-ray
chest (PA) view. In a few (4) cases, we
could aspirate the pleural/ascitic fluid
for cytochemical examination.
Results
The mean age of the 25 cases of dengue fever with CLS was 30.5 ± 15 years, and the
male-female ratio was 1:1.27. The results of testing for dengue fever (NS1 & IgM antibody)
are shown in Table 1. The main clinical findings on admission in the cases of CLS are shown
in Table 2. Fever was present in all (100% cases), generalized body pain in 84% cases, and
bleeding manifestations in 56% cases. Pedal oedema was not present in any of the cases. All
the cases had some degree of thrombocytopenia. The platelet count became normal in all
cases in 4-5 days. No deaths occurred in these cases. The serum albumin levels were mildly
reduced (3.0–3.5 gm/dl) in 80% of cases and significantly reduced (<3.0 gm/dl) in 12% of
cases (Table 2). Urine examination was normal in all the cases.
The findings of the ultrasonographic examination in these cases are shown in Table 3.
Ascites was present in 21 out of 25 cases (84%), pleural effusion in 19 cases (76%) and both
ascites and pleural effusion in 15 cases (60%). The pleural effusion was present on the right
side only in 10 cases (52.6%) (Figure), and both right-sided and left-sided in 9 cases (47.4%).
None of the cases had only left-sided pleural effusion. Mild hepatomegaly and edematous
gall bladder wall was present in 48% and 20% of cases respectively. Pericardial effusion was
not seen in any case.
The estimated fluid volume in peritoneal cavity and pleural space assessed by
ultrasonography are shown in Table 4. In 20 out of 21 cases with ascites, the fluid volume
was less than 1000 ml, and in 18 out of 19 cases with pleural effusion, the volume of fluid
was also below 1000 ml. Therefore, in a majority of cases, the fluid accumulation was mild
to moderate.
In four cases the pleural fluid was aspirated and the findings are shown in Table 5. The
pleural fluid was exudative in all the four cases. There were increased numbers of WBCs
with a preponderance of lymphocytes in all cases and the sugar level in fluid was normal.
Ultrasonography was repeated in all cases after one week. The fluid collection had completely
cleared in 12 cases (48%) and decreased by more than 50% in the remaining cases.
66
Table 2: Clinical findings on presentation in the CLS cases
Finding
Number of patients (%)
(n=25)
Fever
25 (100%)
Generalized body pain
21 (84%)
Bleeding manifestations
14 (56%)
(a)
Petechiae
(b)
Menorrhagia
3 (21.43%)
(c)
Malaena
2 (14.29%)
(d)
Haematuria
1 (7.14%)
(e)
Gum bleeding
1 (7.14%)
7 (50%)
Hypotension
2 (8%)
Altered sensorium (Glasgow coma score = 11)
1 (4%)
Platelet count on admission
(a)
50 000–100 000/mm3
3 (12%)
(b)
20 000–50 000/mm3
15 (60%)
(c)
<20,000/mm3
7 (28%)
Serum albumin
(a)
>3.5 gm/dl
(b)
3.0–3.5 gm/dl
20 (80%)
(c)
<3.0 gm/dl
3 (12%)
2 (8%)
Table 3: Ultrasonographic findings in cases with CLS
Finding
Number of cases (%)
(n=25)
Ascitis
21 (84%)
Pleural effusion
19 (76%)
Both
15 (60%)
Pleural effusion (n=19)
• Right-sided
10 (52.6%)
• Left-sided
Nil (0%)
• Bilateral
9 (47.4%)
67
Figure: X-ray chest PA view of a patient with CLS showing right-sided pleural effusion
Table 4: Volume of ascitis/pleural effusion in the CLS cases (by ultrasonography)
Volume of fluid
Number of patients (%)
Ascitis (n=21)
• <500 ml
11 (52.4%)
• 500–1000ml
9 (42.9%)
• >1000 ml
1 (4.7%)
Pleural effusion (n=19)
• <500 ml
16 (84.2%)
• 500–1000 ml
2 (10.5%)
• >1000 ml
1 (5.3%)
68
Table 5: Findings of pleural fluid examination in cases with CLS
Pleural fluids findings
Case-1
Case-2
Case-3
Case-4
Colour
Straw
coloured
Straw
coloured
Straw
coloured
Straw
coloured
Proteins (gm/dl)
3.3
3.3
3.1
3.4
Total cells/mm3
365
290
320
260
• Polymorphs
27
10
24
18
• Lymphocytes
69
75
73
76
• Monocytes
4
15
3
6
• Eosinophils
Nil
Nil
Nil
Nil
• Sugar
82
112.6
96
108
Differential counts
Discussion
Our results indicate that CLS is not uncommon in dengue fever, being present in approximately
19.7% of cases. Technological advances such as ultrasonography have probably facilitated
the recognition of these cases.[4,5]
The occurrence of fever with ascites/pleural effusion as in our cases can throw up several
diagnostic challenges. Similar findings may occur in tuberculosis and collagen disorders. In
tuberculosis pleural effusion, sometimes the fever may be moderate to high.[6] In collagen
disorders, thrombocytopenia can also occur.
Furthermore, as in tuberculosis pleural effusion, there was lymphocytosis in the fluid
in our cases of CLS. Tuberculosis pleural effusion is common in India and hence many of
these cases can be misdiagnosed and inappropriately given antitubercular treatment. This
distinction is important to be made. Certain points which would favour CLS and help in
distinguishing are as follows:
(1) In CLS, collection of fluid frequently involves multiple sites.
(2) The fluid accumulation is mild to moderate and rarely more than 1000 ml.
(3) The pleural effusion is mainly right-sided and never occurs alone on the left
side.[7]
69
The fluid accumulation in our cases rapidly resolved in a week’s time without any
treatment. In doubtful cases, it would, therefore, be advisable to wait and repeat ultrasound
examination after one week before starting any specific therapy. Appreciation of the
manifestations of CLS due to dengue fever would help in preventing misdiagnosis and
unnecessary treatment.
References
[1] Druey KM, Greipp PP. Narrative review: the systemic capillary leak syndrome. Ann Intern Med. 2010
July 20; 153(2): 90-98.
[2] Kabra SK, Jain Y, Singhal T, Ratageri VH Dengue; hemorrhagic fever: clinical manifestations and
management. Indian J Pediatr. 1999 Jan-Feb; 66(1): 93-101.
[3] Venkata Sai PM, Dev B, Krishnan R. Role of ultrasound in dengue fever. Br J Radiol. 2005 May; 78(929):
416-8.
[4] Quiroz-Moreno R, Méndez GF, Ovando-Rivera KM. Clinical utility of ultrasound in the identification
of dengue hemorrhagic fever. Rev Med Inst Mex Seguro Soc. 2006 May-Jun; 44(3): 243-8.
[5] Srikiatkhachorn A, Krautrachue A, Ratanaprakarn W, Wongtapradit L, Nithipanya N, Kalayanarooj
S, Nisalak A, Thomas SJ, Gibbons RV, Mammen MP Jr, Libraty DH, Ennis FA, Rothman AL, Green S.
Natural history of plasma leakage in dengue hemorrhagic fever: a serial ultrasonographic study. Pediatr
Infect Dis J. 2007 Apr; 26(4): 283-90; discussion 291-2.
[6] Berger HW, Mejia E. Tuberculous Pleurisy. Chest. 1973; 63; 88-92.
[7] Wu KL, Changchien CS, Kuo CH, Chiu KW, Lu SN, Kuo CM, Chiu YC, Chou YP, Chuah SK. Early
abdominal sonographic findings in patients with dengue fever. J Clin Ultrasound. 2004 Oct; 32(8):
386-8.
70
Haemogram profile of dengue fever in adults
during 19 September – 12 November 2008:
A study of 40 cases from Delhi
Sonia Advani,# Shikha Agarwal & Jitender Verma
Department of Biotechnology Engineering, College of Engineering and Technology,
IILM Academy of Higher Learning, Greater Noida, Uttar Pradesh, India.
Abstract
Dengue illness appears similar to other febrile illnesses in its early stages, which means its diagnosis
is often delayed or confused with other illnesses. To address this issue, we analysed the haemogram
profile of 40 patients (>12 years) hospitalized with DHF in Delhi from 19 September to 12
November 2008 to predict outbreaks and severity levels of the disease. Such studies could prove
useful in disease management, diagnosing dengue and predicting the likelihood of haemorrhaging.
All the patients were diagnosed, managed and monitored according to a standard protocol. Of the
40 patients who fulfilled the World Health Organization (WHO) criteria of DHF, 30 (75%) were
male. All patients presented with fever and IgM dengue serology was positive in 100% cases. The
haemogram profile shows that the lymphocyte level is a highly deviated parameter whereas the
red blood corpuscles (RBC) count and mean corpuscular haemoglobin concentration (MCHC) are
the least deviated parameters after performing standard deviation tests.
Keywords: Dengue; Haemogram profile; RBC count; WBC count; MCH; MCHC; Lymphocyte; Delhi.
Introduction
Little is known about the pattern and dynamics of dengue virus in outbreak situations.[1]
Dengue fever is a mosquito-borne flaviviral infection endemic in the tropics and subtropics,
affecting up to 100 million people.[2] Four distinct dengue viral serotypes (DENV-1–4) are
known to cause the illness.[3] The presence of the virus in the blood vessels causes changes
to these blood vessels. The vessels swell and leak. The spleen and lymph nodes become
enlarged and patches of the liver tissue die. A process called disseminated intravascular
coagulation (DIC) can occur.[4] After the virus has been transmitted to the human host, a
period of incubation occurs, and many infections may be asymptomatic. During this time,
the virus multiplies. When present, symptoms of the disease appear suddenly and include
high fever, chills, headache, eye pain, red eyes, enlarged lymph nodes, a red flush to the
face, lower back pain, extreme weakness, and severe aches in the legs and joints. This initial
#
71
Haemogram profile of dengue fever in adults from Delhi
period of illness lasts about two or three days. After this time, the fever drops rapidly and the
patient sweats heavily. After about a day of feeling relatively well, the patient’s temperature
may increase again.[5] The laboratory profile provides the preliminary route to investigation
and the objective of this work was to predict outbreaks and severity levels of the dengue
disease.[6]
Patients admitted with fever, headache, myalgia and retro orbital pains were taken up for the
study. Haemogram profiles of dengue-positive patients were collected with permission from
patients admitted in the Lok Nayak Jai Prakash Narain Hospital, Bhagwati Diagnostic Centre
and Mayur Diagnostic Centre, all in Delhi. Other causes of fever like malaria, leptospirosis,
enteric fever and respiratory infections were excluded by appropriate tests.
Results
Forty patients were evaluated, of which 30 (75%) were male. Dengue fever, headache and
myalgia were the common clinical features. IgM dengue serology was positive in 100%
cases. For all patients, the haemogram profile consisting of various parameters such as mean
corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC),
lymphocyte count, platelet count, white blood cell (WBC) count, red blood corpuscles (RBC)
count, mean corpuscular volume (MCV) and haemoglobin count were tabulated (Table 1).
The deviation of the above parameters from the reference values was calculated by the
method of standard deviation (Table 2). Most patients had a platelet count of between
25 000/mm3 and 50 000/mm3 (56%). The RBC count and MCHC were observed to be the
least deviated parameters in dengue patients whereas lymphocyte count was the highest
deviated parameter. From the data (Table 1), it was also inferred that platelet level is a good
indicator of dengue infection.
Discussion
Dengue fever was noted in adults during 19 September – 12 November 2008. Standard
deviation for each parameters was individually calculated from the normal values, using
formula, Standard deviation (s) = (∑X2/N)1/2 where X = deviation from normal value and
N = number of patients. The most deviated parameter was identified using the above
calculation. Difference in normal values for male and female patients required separate
graphical representations for each parameter.
From Table 2 it was inferred that some parameters are highly deviated and some slightly
deviated. MCH is the least deviated parameter in dengue patients whereas neutrophil is a
72
30.9
30.8
M
M
M
M
M
F
M
F
M
M
F
M
M
M
F
M
F
F
M
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
40.7
33.7
34.1
33.1
33.3
27.2
35.8
32.3
33.1
32.1
34.9
27.1
31.8
32.1
31.3
31.3
32.4
32.5
31.2
F
26.3–33.8
pg/cell
M
Reference
values
MCH
pg/cell
2
Sex
1
Patient
no.
38.6
38.6
35.4
37.5
34.5
36.6
34.8
31.6
37.1
33.79
34.26
32.7
35.5
36
35.5
37.7
30.1
35.2
36.3
36.4
35.9
32–36
g/dl
MCHC
g/dl
42
45
50
53
49
48
49
57
43
46
55
55
40
79
40
64
53
60
60
66
28
140–450
Platelet
×10e3
46
58
46
54
62
53
67
41
45
50
49
42
58
19
57
32
37
37
30
30
22
20–45
Lymphocyte
×10e3
6.2
4.9
5.8
4.7
5.7
11.9
5.7
7.5
7.8
7.9
7.8
5.25
8.7
9.7
8.2
6.5
6.29
4.43
5.1
7
6.9
5000–11 000
WBC count
(x10e3) µl
Table 1: Haemogram profile of 40 dengue patients
2.85
2.17
3.44
3.66
4.49
4.29
4.49
2.26
3.79
3.89
4.44
4.68
3.55
3.49
3.77
1.443
3.55
4.9
5.02
4.52
5.5
5.5±1: M
4±1: F
RBC
(x10e6) µl
102.0
69.5
88.6
88.8
95.5
74.5
95.5
102.2
86.7
83.5
96.4
82.9
87.2
86.2
89.7
85.8
103.9
86.9
89.3
90.7
86.9
80–100 fl
MCV
fL
13.9
9.4
11.6
11.6
14.6
11.7
14.8
12.6
15.4
12.3
15.9
12.7
8.6
10.8
12
12.2
11.1
14.4
14
13
14.2
15.5±2: M
13.5±2: F
HB
73
74
F
40
Reference
values
27.8
32.6
31.7
34.6
39.1
30.9
29.3
28.7
38.8
33.2
40.6
34.8
28.6
31.4
39.3
26.5
32.7
35.6
28.3
26.3–33.8
pg/cell
MCH
pg/cell
37.6
35.4
36.4
38.5
36.8
32.3
31.5
34.9
35.7
37.8
33.7
38.8
31.7
33.2
37.8
36.8
34.3
35.6
37.6
32–36
g/dl
MCHC
g/dl
MCH: Mean corpuscular haemoglobin (picograms/cell).
MCHC: Mean corpuscular haemoglobin concentration (g/dl).
WBC: Count: White blood cell count (x10e3) µl.
RBC: Red blood corpuscles count (x10e6) µl.
M: Male; F: Female.
M
M
33
39
M
32
M
M
31
38
M
30
M
M
29
37
M
28
M
F
27
36
M
26
F
M
25
M
M
24
35
M
23
34
M
22
Patient
no.
Sex
48
46
41
51
47
53
43
49
54
40
59
45
57
41
42
52
50
46
48
140–450
Platelet
×10e3
46
41
49
67
66
59
53
50
62
45
48
42
55
57
43
61
60
44
66
20–45
Lymphocyte
×10e3
5.4
6.7
10.5
5.6
9.8
4.7
6.8
11.6
7.3
5.7
8.9
4.8
10.6
10.2
7.7
6.3
5.5
7.6
7.8
5000–11 000
WBC count
(x10e3) µl
4.58
4.47
3.70
3.28
3.92
3.59
3.13
3.67
3.48
2.79
2.65
2.44
3.80
3.87
4.68
2.88
2.18
3.76
4.22
5.5±1: M
4±1: F
RBC
(x10e6) µl
69.3
86.3
95.7
74.3
102.6
91.5
63.6
101.2
94.8
86.8
97.4
103.8
73.8
68.3
96.7
103.4
70.3
85.3
65.3
80–100 fl
MCV
fL
10.4
9.3
12.7
10.5
14.7
10.13
11.3
13.5
10.8
12.8
9.7
14.6
15.7
13.7
11.4
14.3
15.6
12.5
13.2
15.5±2: M
13.5±2: F
HB
Table 2: Standard deviation for different parameters [this study]
Parameter
Standard deviation
( s)
RBC count
0.89
MCHC
1.71
Haemoglobin
1.91
WBC count
2.02
MCH
3.51
Platelets
8.75
Lymphocyte
11.87
RBC: Red blood corpuscles count.
MCHC: Mean corpuscular haemoglobin concentration.
WBC count: White blood cell count.
MCH: Mean corpuscular haemoglobin.
highly deviated parameter. Platelet count is the most effective way of checking the status
of the dengue patient. This analysis takes into account only some parameters which give a
better insight into the status of the disease.
References
[1] Vaughn DW, Barrett A, Solomon T. Flaviviruses (Yellow Fever, Dengue, Dengue Hemorrhagic Fever,
Japanese Encephalitis, West Nile Encephalitis, St. Louis Encephalitis, Tick-Borne Encephalitis). In: Mandell
GL, Bennett JE, Dolin R, eds. Principles and practice of infectious diseases. 7th ed. Philadelphia: Pa:
Elsevier Churchill Livingstone, 2009. Chap 153.
[2] Gibbons RV, Vaughn DW. Dengue: an escalating problem. BMJ. 2002 29; 324(7353):1 563-6.
[3] Birnbaumer DM. Fever in the Returning Traveler. In: Slaven EM, Stone SC, Lopez FA, eds. Infectious
Infectious diseases: emergency department diagnosis and management. New York: McGraw Hill, 2007.
pp. 418-427.
[4] Ward DI. A case of fatal Plasmodium falciparum malaria complicated by acute dengue fever in East
Timor. Am J Trop Med Hyg. 2006; 75(1): 182-5.
[5] Abrol A, Dewan A, Agarwal N, Galhotra A, Goel NK, Swami HM. A clinico-epidemiological profile of
dengue fever cases in a peri-urban area of Chandigarh. The Internet Journal of Epidemiology. 2007;
5(1).
[6] Goel NK, Gurpreet, Swami HM. Epidemiological characteristics of dengue fever: its prevention and
control. The Internet Journal of Biological Anthropology. 2007; 1(1).
75
Differentiating early adult dengue from acute viral
respiratory infections – A comparative analysis
Tun-Linn Thein,a Eng-Eong Ooi,b,c Jenny GH Lowd & Yee-Sin Leoa#
Department of Infectious Diseases, Communicable Disease Centre, Tan Tock Seng Hospital,
Moulmein Road, Singapore 308433.
a
DSO National Laboratories, 20 Science Park Drive, Singapore 118230.
b
Duke-NUS Graduate Medical School, 8 College Road, Singapore 169857.
c
d
Singapore General Hospital, Outram Road, Singapore 169608.
Abstract
The clinical presentations of dengue disease in adults are not fully described. Differentiating dengue
from other acute viral respiratory infections (ARIs) is important. We conducted a prospective study
from January 2008 to March 2010, recruiting subjects with early febrile illness presenting within
the first 72 hours of illness at primary care outpatient clinics. This study evaluates cases enrolled
to identify distinguishing clinical features of early dengue infection from ARIs.
Acute and convalescent venous blood and nasal swab specimens were collected. Dengue was
confirmed by RT-PCR, virus isolation, IgM/IgG seroconversion or fourfold IgG titre increase in
paired blood samples. Non-dengue cases were tested for respiratory viruses from nasal swabs by
RT-PCR.
Dengue was confirmed in 49 patients along with 151 cases of influenza, 10 of parainfluenza
and 29 patients of other viruses. The demographics between dengue (n=49) and PCR-positive
viral ARI cases (n=190) did not differ significantly except by age (mean 39.1 years vs 33.7 years
respectively; P<0.05). Compared with other viral ARIs, dengue patients had significantly more
frequent joint pain, vomiting, red eyes, rashes and longer symptoms duration. In the multivariate
model, red eyes and leucopenia significantly differentiate between the two groups (P<0.01). This
study provides information for early recognition of dengue infection.
Keywords: Adult dengue; Acute viral respiratory infections (ARIs).
Introduction
Dengue is the most important mosquito-borne viral infection of humans. Worldwide, an
estimated 2.5 billion people living in urban areas in tropical and subtropical countries are
at risk of dengue infection.[1] Dengue is caused by four closely-related virus serotypes of the
#
76
Adult dengue and acute viral respiratory infections
genus Flavivirus. Disease spectrum varies from asymptomatic to severe dengue with fatal
clinical outcomes, characterized by plasma leakage leading to shock.[2]
Dengue re-emerged in Singapore in recent decades despite aggressive vector control.
Predominantly a disease of children in the past, it has become an increasingly-recognized
problem in adults.[3-5] Early clinical presentations of dengue disease in adults are, however,
poorly described. Dengue virus infections are often difficult to distinguish clinically from
other acute febrile illnesses, including influenza and other influenza-like illnesses. The ability
to suspect and diagnose dengue during its early course of illness is critical for clinicians in
order to institute appropriate care and monitoring of the patients.[6]
We conducted a prospective study of acute febrile patients comparing dengue and other
acute viral respiratory infections (ARIs) to characterize early clinical presentations of dengue
in adults and identify early clinical features distinguishing dengue from viral ARIs.
This study prospectively recruited adults aged 18 years and above, who consented to the study,
with early undifferentiated fever within 72 hours of onset.[7] All subjects were recruited from
four primary health care facilities in Singapore from January 2008 to March 2010. Venous
blood and nasal samples were taken at 1–3 days (1st visit) and 4–7 days (2nd visit) after the
onset of fever. Convalescent blood sample was collected 3 weeks (3rd visit) later. Demographic,
epidemiological and clinical data were collected using structured questionnaires by the
research nurses.[7,8] The National Healthcare Group Domain Specific Review Board (DSRB
B/05/013) approved the study.
Dengue infection was confirmed by real-time reverse transcription-polymerase chain
reaction (RT-PCR),[9] virus isolation, IgM/IgG sero-conversion or fourfold IgG titre increase
in paired blood samples.[8,10] Non-dengue cases were tested for respiratory viruses by direct
immunoflorescence assay and RT-PCR from nasal swabs.[11,12] A bench-top Food and Drug
Administration (FDA)-approved haematocytometer (iPoch-100, Sysmex, Japan) was used
for haematology assessment.
Chi-square test and Fisher’s exact tests were used to examine the association between
categorical variables and diagnostic values. For continuous variables, two-tailed independent
t-test was used. Univariate analysis was performed to determine statistical difference
between dengue and acute viral respiratory infections (ARIs), as well as between dengue
and other febrile illnesses (OFIs). Multiple logistics regression was also applied to identify
the independent predicting factors between dengue and viral ARIs. Receiver operating
characteristic analysis was performed to evaluate the predictive model. Data were analysed
by using the computer-based SPSS version 16 (SPSS Inc., Chicago, IL, USA). P value less
than 0.05 was considered as significant.
77
Results
A total of 691 patients with acute febrile illness were recruited during the study period.
Dengue infection was confirmed in 49 (7.1%) patients, 190 (27.5%) patients were confirmed
for acute viral respiratory infections (ARIs) and 452 (65.4%) patients were confirmed for
other febrile illnesses (OFIs). ARI cases were further identified to be 151 of influenza, 10
of parainfluenza and 29 of other viruses. Twenty-nine out of 49 dengue cases had dengue
EIA or Capture IgG-positive at the first visit or within the first three days of illness, indicating
secondary dengue infection. Dengue IgG in acute blood samples also tested positive in
27.4% of ARI cases and 30.5% of OFI cases, reflecting dengue endemicity in Singapore. The
demographics between dengue and PCR-positive viral ARI cases did not differ significantly
except by age (mean 39.1 years vs 33.7 years respectively; P<0.05). No statistical difference
was found between the demographics of dengue and OFIs (Table 1). Sixteen (33%) dengue
patients required in-patient care in contrast with 1 (0.53%) of viral ARI and 12 (2.7%) of
OFIs. No mortality was recorded in the cohort.
Compared with viral ARIs and OFIs, dengue patients had significantly more frequent joint
pain, red eyes and longer symptom durations. Vomiting was present in a significantly higher
proportion of dengue patients compared to ARI but not OFI cases. Dengue patients had a
significantly higher mean aural temperature and more frequent nausea compared to OFIs,
but not ARIs. The frequency of abdominal pain, bleeding and nausea was not significantly
different between the groups. Significantly lower mean white cell counts and platelet counts
were observed in dengue patients than in the other two groups (Table 2).
In the multivariate model for dengue and ARIs, having red eyes (relative risk 3.8, P<0.01)
and leucopenia (relative risk 5.6, P<0.1) were independent predicting factors for dengue
infection. The receiver operating characteristic (ROC) analysis for the model revealed that
the area under the (ROC) curve to differentiate dengue from ARI was 0.83 (P<0.001), and
had 93.9% sensitivity and 51.0% specificity.
Discussion and conclusion
Dengue is the most rapidly spreading mosquito-borne viral disease which constitutes a public
health emergency of international concern. In Singapore, together with other countries in the
World Health Organization’s Western Pacific Region, dengue has been identified as a major
public health issue.[6] In the year 2008 and 2009, 7031 and 4497 dengue cases respectively
were notified to Singapore’s health care system, of which 93.7% were older than 15 years
of age in both years.[5,13]
Because dengue has become predominantly an illness affecting adults, this prospective
cohort study was designed to recruit 18-year-old and older patients with undifferentiated fever
less than 72-hours duration. All patients were recruited from primary health care facilities in
78
Table 1: Demographic characteristics of patients having dengue and
acute viral respiratory infections (ARI) in Singapore
Dengue
(N=49)
ARI
(N=190)
P
values
OFI
(N=452)
P
values
Mean age + SD
39.1 ± 14.8
33.7 ± 15.1
0.026
35.1 ± 15.0
0.077*
Males
31
(63.3)
118
(62.1)
0.510
291
(64.4)
0.078
0.134
Ethnicity
0.496
Chinese
33
(67.3)
96
(50.5)
259
(57.3)
Indian
7
(14.3)
35
(18.4)
66
(14.6)
Malay
3
(6.1)
32
(16.8)
93
(20.6)
Others
6
(12.2)
27
(14.2)
34
(7.5)
Singaporeans
30
(61.2)
125
(65.7)
0.615
317
(70.1)
0.197
Travel history
9
(18.3)
22
(11.6)
0.234
58
(12.8)
0.272
Condominium
0.420
0.689
Type of housing
2
(4.1)
13
30
(6.8)
(6.6)
Dormitory/Hostel
1
(2.0)
1
(0.5)
4
(0.9)
Flat, HDB
36
(73.5)
144
(75.8)
364
(80.5)
Landed
7
(14.3)
19
(10.0)
32
(7.1)
Worksite
3
(6.1)
13
(6.8)
19
(4.2)
Reported past dengue
4
(8.2)
6
(3.2)
0.094
23
(5.1)
0.323
Co-morbidities
6
(12.2)
23
(12.1)
0.572
61
(13.5)
0.918
All P values shown are analysed in comparison to dengue, using Chi-square test and Fisher’s exact test unless
otherwise indicated.
*Independent t-test was used.
Variables shown are numbers with percentage in parentheses unless otherwise stated.
SD=standard deviation, HDB=Housing & Development Board.
Singapore between January 2008 and March 2010. Among the 691 patients, 7.1% patients
were confirmed to have dengue infection by dengue PCR or IgM sero-conversion in paired
blood samples, while acute viral respiratory infections (ARIs) and other febrile illnesses (OFIs)
were diagnosed in 27.5% and 65.4% patients respectively. Among the dengue cases reported
to the Ministry of Health during 2008 and 2009, on an average, there were 61.3% males,
51.2% Chinese, 64.8% local Singaporeans and 58.9% Housing & Development Board (HDB)
flat residents.[5,13] Comparable demographic characteristics among the confirmed dengue cases
in our study showed representation of national distributions. In our study, the prevalence of
co-morbidities was similar between dengue, ARI and OFI cases. Co-morbidities included
79
Table 2: Clinical and laboratory features of dengue and
acute viral respiratory infections in Singapore
Dengue
(N=49)
ARI
(N=190)
P
values
OFI
(N=452)
P
values
38.4 ± 0.8
38.2 ± 2.3
0.69
38.1 ± 0.8
0.005*
SBP (mmHg) ± SD
117.3 ± 18.1
122.0 ± 14.6
0.06
119.5 ± 16.4
0.384*
Pulse rate per minute ± SD
91.2 ± 14.2
95.0 ± 14.8
0.10
90.2 ± 14.5
0.666*
Drowsiness
24
(49.0)
112
(58.9)
0.314
259
(57.3)
0.462
Headache
38
(77.6)
151
(79.5)
0.823
315
(69.7)
0.503
Muscle pain
33
(67.3)
130
(68.4)
0.506
297
(65.7)
0.477
Joint pain
29
(59.2)
73
(38.4)
0.007
168
(37.2)
0.002
Loss of appetite
36
(73.5)
129
(67.9)
0.684
300
(66.4)
0.563
Abdominal pain
12
(24.5)
36
(18.9)
0.249
95
(21.0)
0.772
Diarrhea
6
(12.2)
13
(6.8)
0.169
39
(8.6)
0.269
Nausea
24
(49.0)
63
(33.2)
0.112
133
(29.4)
0.019
Vomiting
8
(16.3)
11
(5.8)
0.022
47
(10.4)
0.410
Red eye
18
(36.7)
31
(16.3)
0.002
66
(14.6)
<0.001
Rashes
6
(12.2)
0
(0)
<0.001
18
(4.0)
0.033
Retro orbital pain
8
(16.3)
41
(21.6)
0.623
60
(13.3)
0.797
Swollen lymph node
1
(2.0)
12
(6.3)
0.329
30
(6.6)
0.374
Taste alteration
37
(75.5)
126
(66.3)
0.400
274
(60.6)
0.119
Skin sensitivity
11
(22.4)
31
(16.3)
0.210
70
(15.5)
0.413
Bleeding
1
(2.0)
5
(2.6)
0.643
11
(2.4)
0.669
Haematocrit (%)± SD
46.2 ± 9.4
46.1 ± 8.8
0.99
46.1 ± 8.6
0.947*
Haemoglobin (g/dL) ± SD
15.3 ± 3.3
15.1 ± 2.8
0.62
15.2 ± 2.8
0.711*
WBC (103/mL ) ± SD
4.4 ± 2.2
7.0 ± 2.8
<0.001
8.6 ± 4.3
<0.001*
159.2 ± 76.1
216.6 ± 77.7
<0.001
240.7 ± 115.7
<0.001*
9.2 ± 3.9
7.4 ± 5.0
0.02
6.0 ± 4.3
<0.001*
Temperature (°C) ± SD
Platelet (103/mL ) ± SD
Symptom duration days ± SD
All P values shown are analysed in comparison to dengue, using Chi-square test and Fisher’s exact test unless
otherwise indicated.
*Independent t-test was used.
Variables shown are numbers with percentage in parentheses unless otherwise stated.
ARI=acute viral respiratory infections, OFI=other febrile illnesses.
SD=standard deviation, SBP=systolic blood pressure, WBC=white blood cell count.
80
diabetes, ischaemic heart disease, malignancy and steroid-treated diseases. Some patients
had more than one pre-existing co-morbidities.
Compared to viral ARI patients, dengue patients were older. In this cohort, having red
eyes was an independent predicting factor for dengue infection. In India, a study revealed
that 37.3% of adult dengue inpatients were reported to have subconjunctival haemorrhage,[14]
while a paediatric study from Viet Nam reported that headache was the most common
presenting symptom, followed by conjunctivitis, petechial rash, muscle and joint pain, nausea
and abdominal pain.[15] Frequencies of abdominal pain among dengue and viral ARI patients
were not different in our cohort. A study from Thailand reported that positive tourniquet
test and presence of leucopenia can predict dengue diagnosis.[16] Although tourniquet test
is commonly performed to differentiate dengue haemorrhagic disease from OFI, the test is
not performed in Singapore.[17] Tanner et al. reported a decision algorithm for the diagnosis
of dengue using a combination of platelet count, total white cell count, body temperature,
absolute lymphocyte and neutrophil counts.[18] Using fever and leucopenia to predict the
diagnosis of dengue was discussed in a larger cohort of older adults presenting with febrile
illness in Singapore.[8] Our study further supports leucopenia (WBC <4.5x103/mL) as a useful
laboratory feature for differentiating dengue from viral ARIs.
Dengue is a disease with a wide spectrum of clinical presentations and often with
unpredictable clinical evolution and outcome. It is often difficult to distinguish dengue
clinically from other viral ARIs. While other diseases such as chikungunya may mimic dengue
infection,[6] none of our subjects in this cohort tested positive for chikungunya virus using inhouse PCR[19] on acute febrile samples. In resource-limited areas where laboratory diagnostic
tests are costly or are not available, and access to rapid tests is not consistent, our study
supported the use of clinical sign (red eye) and peripheral white cell count to differentiate
patients with dengue from acute viral respiratory illness during the early stage. A case report
highlighted co-infection of dengue and influenza presenting with undifferentiated febrile
illness.[20] Our study did not assess co-infection as only those tested negative for dengue were
analysed for respiratory pathogens. However, this phenomenon can be further explored.
From our study, it was found that a significantly higher proportion of dengue patients
than viral ARIs patients required inpatient care. Dengue patients remained symptomatic for
a longer duration than those with viral ARIs. This has implication for the loss of productive
days among adults. We hope information from our study may help identify dengue early
for appropriate management.
Acknowledgements
This study was supported by the National Medical Research Council of Singapore (NMRC/
TCR/005/2008). The authors thank the doctors of the polyclinics for their referral of patients,
and research nurses for their assistance in data and clinical sample collection.
81
References
[1] Guzman MG, Halstead SB, Artsob H, Buchy P, Farrar J, Gubler DJ, et al. Dengue: a continuing global
threat. Nat Rev Microbiol. 2010 Dec; 8(12): S7-S16.
[2] Gubler DJ. Dengue and dengue hemorrhagic fever. Clin Microbiol Rev. 1998 Jul;11(3): 480-96.
[3] Ooi EE, Goh KT, Gubler DJ. Dengue prevention and 35 years of vector control in Singapore. Emerg
Infect Dis. 2006 Jun; 12(6): 887-93.
[4] Ler TS, Ang LW, Yap GSL, Ng LC, Tai JC, James L, et al. Epidemiological characteristics of the 2005 and
2007 dengue epidemics in Singapore -similarities and distinctions. Western Pacific Surveillance and
Response Journal. 2011; 2(2): doi: 10.5365/wpsar.2010.1.1.011.
[5] Communicable disease surveillance in Singapore 2009. Singapore: Ministry of Health, 2010.
[6] World Health Organization. Dengue: guidelines for diagnosis, treatment, prevention and control.
Geneva: World Health Organization, 2009.
[7] Low JG, Ooi EE, Tolfvenstam T, Leo YS, Hibberd ML, Ng LC, et al. Early Dengue infection and outcome
study (EDEN) - study design and preliminary findings. Ann Acad Med Singapore. 2006 Nov; 35(11):
783-9.
[8] Low JG, Ong A, Tan LK, Chaterji S, Chow A, Lim WY, et al. The early clinical features of dengue in
adults: challenges for early clinical diagnosis. PLoS Negl Trop Dis. 2011; 5(5): e1191.
[9] Lai YL, Chung YK, Tan HC, Yap HF, Yap G, Ooi EE, et al. Cost-effective real-time reverse transcriptase
PCR (RT-PCR) to screen for Dengue virus followed by rapid single-tube multiplex RT-PCR for serotyping
of the virus. J Clin Microbiol. 2007 Mar; 45(3): 935-41.
[10] Chaterji S, Allen JC, Chow A, Leo YS, Ooi EE. Evaluation of the NS1 Rapid Test and the WHO Dengue
Classification Schemes for Use as Bedside Diagnosis of Acute Dengue Fever in Adults. Am J Trop Med
Hyg. 2011 Feb; 84(2): 224-8.
[11] Watzinger F, Suda M, Preuner S, Baumgartinger R, Ebner K, Baskova L, et al. Real-time quantitative
PCR assays for detection and monitoring of pathogenic human viruses in immunosuppressed pediatric
patients. J Clin Microbiol. 2004 Nov; 42(11): 5189-98.
[12] Templeton KE, Scheltinga SA, Beersma MF, Kroes AC, Claas EC. Rapid and sensitive method using
multiplex real-time PCR for diagnosis of infections by influenza a and influenza B viruses, respiratory
syncytial virus, and parainfluenza viruses 1, 2, 3, and 4. J Clin Microbio. 2004 Apr; 42(4): 1564-9.
[13] Communicable Disease Surveillance in Singapore 2008. Singapore: Ministry of Health, 2009.
[14] Kapoor HK, Bhai S, John M, Xavier J. Ocular manifestations of dengue fever in an East Indian epidemic.
Can J Ophthalmol. 2006 Dec; 41(6): 741-6.
[15] Buchy P, Vo VL, Bui KT, Trinh TX, Glaziou P, Le TT, et al. Secondary dengue virus type 4 infections in
Vietnam. Southeast Asian J Trop Med Public Health. 2005 Jan; 36(1): 178-85.
[16] Kalayanarooj S, Nimmannitya S, Suntayakorn S, Vaughn DW, Nisalak A, Green S, et al. Can Doctors
Make an Accurate Diagnosis of Dengue Infections at an Early Stage? Dengue Bull. 1999; 23: 1-7.
82
[17] Leo YS, Thein TL, Fisher DA, Low JGH, Oh HM, Narayanan RL, et al. Confirmed adult dengue deaths
in Singapore: 5-year multi-center retrospective study. BMC Infect Dis. 2011 May 12; 11(1): 123.
[18] Tanner L, Schreiber M, Low JG, Ong A, Tolfvenstam T, Lai YL, et al. Decision tree algorithms predict
the diagnosis and outcome of dengue fever in the early phase of illness. PLoS Negl Trop Dis. 2008;
2(3): e196.
[19] Ng LC, Tan LK, Tan CH, Tan SS, Hapuarachchi HC, Pok KY, et al. Entomologic and virologic investigation
of Chikungunya, Singapore. Emerg Infect Dis. 2009 Aug; 15(8): 1243-9.
[20] Lopez Rodriguez E, Tomashek KM, Gregory CJ, Munoz J, Hunsperger E, Lorenzi OD, et al. Co-infection
with dengue virus and pandemic (H1N1) 2009 virus. Emerg Infect Dis. 2010 May; 16(5): 882-4.
83
Evaluation of an immunochromatographic test for
early and rapid detection of dengue virus infection
in the context of Bangladesh
Rabeya Sharmin,a# Shahina Tabassum,b Munira Jahan,b
Afzalun Nessab & K.Z. Mamuna
Department of Virology, Dhaka Medical College, Dhaka, Bangladesh.
a
Department of Virology, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh.
b
Abstract
Early, accurate and rapid diagnosis of dengue virus infection is important for early case management
and for reducing its associated complications, DHF/DSS. In this study, an early and rapid diagnosis
of dengue virus infection was performed from single serum samples by two serological methods.
Blood samples collected from a total of 201 clinically-suspected dengue fever patients were tested
for IgM and IgG antibodies by a rapid immunochromatographic test (ICT), and also by IgM and
IgG antibody Capture ELISA. Of these, 126 (62.7%) patients tested positive for dengue antibodies
by ICT, of which 70 (55.6%) were primary and 56 (44.4%) were secondary cases. By ELISA, 137
(68.2%) tested positive for dengue antibodies, of which 80 (58.4%) were primary and 57 (41.6%)
were secondary cases. Before 5 days of fever, 20.2% primary and 10.1% secondary dengue
infections were detected by ICT, while 30.3% primary and 12.6% secondary dengue infections
were detected by ELISA. At day 5 of fever, ICT detected 42.8% cases as primary and 34.7% as
secondary dengue infections, but ELISA detected 51.0% primary and 32.6% secondary infections.
After 5 days of fever, ICT detected primary dengue infection in 45.2% cases and secondary infection
in 42.5% cases, while ELISA detected 42.5% primary dengue infection and 42.5% secondary
infection. When compared with ELISA, ICT showed 86.7% sensitivity and 96.5% specificity for
IgM detection, whereas for IgG it was 94.7% and 98.6% respectively.
Keywords: Dengue fever; Dengue haemorrhagic fever; ICT; ELISA; Bangladesh.
Introduction
Dengue fever/dengue haemorrhagic fever (DF/DHF) continues to be the most important
arboviral disease of mankind.[1,2] Compared with nine reporting countries in the 1950s, today
the geographical distribution of dengue has spread to more than 100 countries worldwide,
#
84
Immunochromatographic test for rapid detection of dengue virus infection in Bangladesh
with South-East Asia and the Western Pacific regions being the most seriously affected
areas.[3,4] Two-fifths of the world’s population is now at the risk of dengue, with approximately
50 million new cases occurring annually.[5]
The first reported outbreak of dengue in Bangladesh was called the “Dacca fever”
recorded in 1964.[6,7] Subsequent reports suggested that DF and DHF may have been occurring
sporadically in Bangladesh.[8-11] Dengue virus infections may be asymptomatic or may cause
undifferentiated febrile illness (viral syndrome), dengue fever (DF), or dengue haemorrhagic
fever (DHF) including dengue shock syndrome (DSS).[2,3]
Primary infection with one of the four serotypes confers life-long immunity to that
serotype. Secondary infection with a different serotype is associated with an increased risk of
DHF. Primary dengue virus infection is characterized by elevation in specific immunoglobulin
M (IgM) levels 3-5 days after the onset of symptoms and subsequent rise for the next 1-3
weeks. This particular IgM can persist in blood for more than 2-3 months.[12,13] Immunoglobulin
G (IgG) is detectable at low titres at the end of the first week of illness, increasing slowly and
may persist for life in low titre. In secondary infection, approximately 5% of patients do not
produce detectable levels of specific IgM, and the IgM titre rises slowly. However, in secondary
infection, IgG appears approximately two days after the symptoms appear and is detectable
at significantly higher titres which may persist for 10 months to the rest of life.[13,14,15]
Since the prevalence of dengue has increased dramatically in recent decades, its
early and rapid diagnosis will obviously lead to a better management of affected patients.
The laboratory diagnosis of dengue infection is based on three approaches, namely, virus
isolation, serology and molecular techniques, e.g. the polymerase chain reaction (PCR).[12,15,16]
Serology is the mainstay for the diagnosis of dengue infection in most routine laboratories in
developing countries as it is rapid, easier to perform and is less costly.[12,17] ELISA has been
successfully applied for years to detect and distinguish IgG and IgM antibodies to dengue
and other flaviviruses[14,16] and is the most effective diagnostic method in large outbreaks.[14,18]
Recently, IgM and IgG Capture ELISA have been modified into immunochromatographic
formats in which the results of the assay are detected by a colour change visible to the naked
eye. Rapid immunochromatographic test (ICT) relies on both immunoglobulin M (IgM) and
immunoglobulin G (IgG) detection to diagnose active dengue virus infection[12,19] and has
the potential for use at the point of care or in laboratories where the volume of testing is
less or sporadic and where appropriate equipments such as, ELISA, PCR, cell culture, etc.,
are not available.[20]
This study, conducted in 2008, covered 201 clinically-suspected dengue fever patients
selected from different hospitals of Dhaka city, Bangladesh, and from patients visiting the
Department of Virology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka,
85
for dengue antibody testing. Dengue fever cases were selected on the basis of ‘‘WHO criteria
for case definition of dengue fever, dengue haemorrhagic fever, dengue shock syndrome’’
(National Guidelines for Clinical Management of Dengue Syndrome, Bangladesh, 2000).
Blood samples were collected from July to October. All serum samples were tested to detect
dengue virus-specific IgM and IgG antibodies by ICT and antibody Capture ELISA.
Capture ELISA
For dengue IgM and IgG Capture ELISA, Dengue IgM and IgG Capture ELISA kits (Panbio
Diagnostics, Australia, Catalog No. E-DEN0IM and E-DEN02G) were used according to the
manufacturer’s instructions.
Immunochromatographic test
Panbio Dengue Duo Cassette (Panbio Diagnostics, Australia, Catalog No. R-DEN03D) was
used according to the manufacturer’s instructions, and both IgM and IgG antibodies were
determined using a capture assay format.
Data analysis
Data obtained from the study were analysed and the significance of difference was estimated
by using the computer-aided statistical package (SPSS) version 15. Comparison between
groups was done by chi-square test and correlation coefficient test as applicable. Probability
less than 0.05 was considered as significant.
Results
The serological diagnosis among the 201 clinically-suspected dengue fever patients by ICT
detected 126 (62.7%) and the ELISA test detected 137 (68.2%) dengue antibody-positive
cases. Of the 126 positive cases detected by ICT, 70 (55.6%) were positive for only IgM
antibody, 5 (3.9%) were positive for only IgG antibody, and 51 (40.5%) were positive for
both IgM and IgG antibodies. Among the 137 ELISA-positive cases, IgM was detected in
80 (58.4%) patients, IgG in 2 (1.5%) patients, and both IgM and IgG was detected in 55
(40.1%) patients (Table 1).
Of the 79 patients tested before 5 days of fever, primary dengue infection was detected
in 16 (20.2%) and secondary dengue infection in 8 (10.1%) cases by ICT. However, by
ELISA, 24 (30.3%) cases were detected as primary and 10 (12.6%) cases as secondary
dengue infections. Out of the 49 patients who were tested at day 5 of fever, 21 (42.8%)
were detected as primary and 17 (34.7%) as secondary dengue infection by ICT, whereas by
86
Table 1: IgM and IgG antibodies determined by ELISA and ICT in dengue fever patients in
Dhaka, Bangladesh, 2008
ELISA
ICT
No. of cases
No. of cases
Only IgM
80 (58.4%)
70 (55.6%)
Only IgG
2 (1.5%)
5 (3.9%)
Both IgM & IgG
55 (40.1%)
51 (40.5%)
Total positive
137 (68.2%)
126 (62.7%)
Negative
64 (31.8%)
75 (37.3%)
Type of antibody
ELISA, 25 (51.0%) were detected as primary and 16 (32.6%) as secondary dengue infections.
Among the 73 patients tested after 5 days of fever, ICT detected primary dengue infection in
33 (45.2%) cases and secondary dengue infection in 31 (42.5%) cases, while ELISA detected
31 (42.5%) primary dengue infection and 31 (42.5%) secondary dengue infection (Table 2).
No significant difference was observed between primary and secondary dengue cases with
regard to the duration of fever by ICT and ELISA (p = 0.136 for ICT; p = 0.446 for ELISA).
With the rapid ICT, 119 (59.3%) samples tested positive for dengue IgM antibody and
56 (27.9%) samples tested positive for dengue IgG antibody. Using the focus ELISA as the
gold standard, the sensitivity, specificity and positive predictive values and the negative
predictive value determined for IgM were 86.7%, 96.5%, 98.3% and 75.3% respectively,
while for IgG, these were 94.7%, 98.6%, 96.4% and 97.9% respectively (Table 3). A positive
correlation was observed between ELISA and ICT for IgM (r=0.768) and IgG (r=0.753)
respectively (Figure).
Table 2: Relation of duration of fever with antibody detection among primary and
secondary dengue cases, Dhaka, Bangladesh, 2008
Duration of fever
Dengue ICT
Dengue ELISA
Primary
Secondary
Primary
Secondary
70 (34.8%)
56 (27.9%)
80 (39.8%)
57 (28.3%)
< 5 days (n=79)
16 (20.2%)
8 (10.1%)
24 (30.3%)
10 (12.6%)
5 days (n=49)
21 (42.8%)
17 (34.7%)
25 (51.0%)
16 (32.6%)
> 5 days (n=73)
33 (45.2%)
31 (42.5%)
31 (42.5%)
31 (42.5%)
Total (n=201)
p value = 0.446 for ICT and p value = 0.136 for ELISA.
*Chi-square test was done to measure the level of significance.
87
Table 3: Results of ICT compared to ELISA for detection of IgM and IgG antibodies,
Dhaka, Bangladesh, 2008
ICT
ELISA(IgM)
Positive
Negative
Positive
117
2
Negative
18
55
ICT
ELISA(IgG)
Positive
Negative
Positive
54
2
Negative
3
142
Sensitivity
Specificity
PPV
NPV
86.7%
96.5%
98.3%
75.3%
Sensitivity
Specificity
PPV
NPV
94.7%
98.6%
96.4%
97.9%
PPV - Positive predictive value.
NPV- Negative predictive value.
Figure: Correlation between the results of IgM and IgG by ICT and ELISA. Here, result for
ELISA was quantitative and for ICT categorical variable (0 = negative and 1= positive).
Positive r value indicates positive correlation
12.00
Point biserial correlation, r=0.753, p=0.001
10.00
10.00
Point bicerial correlation, r=0.768, p=0.001
8.00
ELISA IgG
ELISA IgM
8.00
6.00
4.00
6.00
4.00
2.00
2.00
0.00
0.00
0.00
0.20
0.40
0.60
ICT IgM
0.80
1.00
0.00
0.20
0.40
0.60
0.80
1.00
ICT IgG
Discussion
Dengue fever is a major public health problem throughout the world. The severe form of
the disease is a leading cause of hospitalization and death among children and adults in
many south-east Asian countries including Bangladesh. Therefore, there is an urgent need
88
for a rapid, reliable and early diagnostic test for dengue surveillance, especially in countries
where dengue is endemic. Due to higher mortality associated with secondary dengue cases,
it is important to use diagnostic assays that are able to differentiate between primary and
secondary dengue infections. As primary and secondary dengue infections show markedly
different immunological responses, detection of antibodies is a valuable procedure to diagnose
and differentiate between dengue infections.[2,13,14].
In this study, Panbio ELISA IgG/IgM and Panbio ICT were used to evaluate early and
rapid diagnosis of dengue virus infection. A comparison was also done between rapid ICT
and IgM and IgG antibody Capture ELISA for dengue virus-specific IgM and IgG antibodies
from serum samples. The two commercial tests used in this study are both suitable for the
detection of anti-dengue IgM and IgG antibodies. ELISA is more appropriate for routine
diagnostic laboratories where large numbers of samples are tested, while the rapid test
may have greater utility in peripheral health settings where relatively fewer specimens are
processed. Both tests use the combined determination of IgM and IgG antibodies in dengue
diagnosis according to the manufacturer’s instructions, and interpretations are made as
primary, secondary or ‘no dengue’ infection. The values of these methods have been reported
previously.[21] Total assay time for the rapid test is 15 min, while the ELISA takes just over
3 hours to complete. The IgM and IgG antibody Capture ELISA is very quick compared to
other dengue ELISAs reported previously.[14,22,23] In Capture ELISA, the incubation of serum
in the anti-human antibody plate is done simultaneously when peroxidase conjugated
monoclonal antibody with antigen is left at room temperature. This decreases the number
of assay steps and speeds up the diagnosis.[21] Furthermore, both the rapid ICT and ELISA are
convenient to use as antigen is provided in a stable dry form and all reagents are provided
in the ready-to-use form.
In the combined use of IgM and IgG Capture ELISA, the cut-off value of the IgG ELISA
is generally set to differentiate between the high levels of IgG characteristic of secondary
infections and the lower IgG levels characteristic of primary or past dengue infections. With
this combination, the majority of secondary dengue virus infections are detected on the basis
of IgG, and most of them also show an elevation of IgM. In contrast, the majority of primary
dengue virus infections show an elevation of IgM but not of IgG.[18,22,24] In rapid ICT, the IgG test
line is set to detect high levels of IgG characteristic of secondary virus infection (HI≥1:2,560)
and hence is able to distinguish between secondary and primary and past dengue infections.
The IgM test line is set to detect IgM levels characteristically present in primary dengue virus
infections and in the majority of secondary dengue virus infections.[21,22]
In our study, 62.7% of patients were positive for dengue antibodies by ICT and 68.2%
were positive by ELISA. A total of 55.6% primary and 44.4% secondary dengue cases were
detected by ICT, whereas 58.4% primary and 41.6% secondary dengue cases were detected
by ELISA. Previous studies from Bangladesh have detected 71%, 65% and 78% secondary
89
infections and remaining 29%, 35% and 22% primary infections respectively by ELISA.[8,11].
Identification of secondary infection early during an acute phase of illness is valuable for the
clinician as proper management can be started early, thereby decreasing the risk of progression
to life-threatening DHF and DSS and hence reducing the case-fatality rate.
The detection rate of dengue in this study was relatively less before five days of fever
by both ICT and ELISA, but ELISA detected more primary cases (30.3%) than ICT (20.2%).
However, the detection rate of secondary dengue infection was almost the same by the
two methods. Failure to identify dengue-specific IgM or IgG antibodies during the first 5 to
7 days of illness does not eliminate dengue virus as the etiology of the illness, and, as such,
follow-up testing is important.[25] Although the majority of patients in our study developed
dengue-specific antibodies from day 5 and onwards of illness, many dengue-infected patients
did not follow this trend. By combining the results of IgM and IgG Capture ELISA, 79% of the
patients were tested before five days of fever while 82% were positive when tested on day
5 of illness.[22] A study from Thailand observed that nearly 80% of patients with dengue virus
infection were detected four days after the onset of symptoms, and this rose to over 90%
by day 5.[26] Similarly, other studies have also detected that most dengue patients produced
dengue-specific antibodies by day 5 of illness.[12,22,27] Therefore, these cases would have been
interpreted as negative if they were not re-tested after five days. Thus, for the detection of
dengue-specific antibodies, patients should be tested from day 5 of fever and onwards.[28]
The rapid ICT showed good sensitivity and specificity in our study which is comparable
to IgM and IgG Capture ELISA. Moreover, a positive correlation was observed between
ELISA and ICT. While some studies have reported very high (99%–100%) sensitivity and
(88%–96%) specificity of rapid test (ICT) for dengue diagnosis,[22,29] other studies have reported
45.8%–67% sensitivity and 33.3%–53.8% specificity.[28,30] In another study using Panbio ICT,
IgM showed 67.3% sensitivity, 91.7% specificity, 89.7% positive predictive value and 72.1%
negative predictive value, while IgG showed 66.4% sensitivity, 94.4% specificity, 97% positive
predictive value and 51.0% negative predictive value.[19] Other studies also offer a conclusion
in favour of rapid ICT.[29,31] Thus, dengue rapid ICT may be a useful tool in the diagnosis of
dengue fever as it is rapid, easy to perform and can be used in settings where laboratory
equipments such as ELISA, PCR or cell culture are not available.
Our study showed that most patients were not very keen to visit the hospital again to
be re-tested as they recover within seven days of their first test. Therefore, early and rapid
diagnosis of dengue virus infection from a single serum sample is extremely important. Single
serum samples are convenient for identifying most of the dengue cases by both ELISA and
ICT methods. However, for early diagnosis, and where laboratory equipments are available,
ELISA is more suitable than ICT.
90
Acknowledgments
We would like to thank Dr B.K. Sil, MP Biomedical Asia Pacific Pte Ltd., Singapore,
for supplying Panbio Dengue Duo Cassette (Panbio Diagnostics, Australia, Catalog No.
R-DEN03D).
References
[1] Guzman MG, Kouri G. Dengue diagnosis advances and challenges. Int J Infect Dis. 2004; 8: 69-80.
2nd edition. Geneva: WHO, 1997. http://www.who.int/csr/resources/publications/dengue/itoviii.pdf accessed 11 January 2012.
[3] Gubler DJ. Dengue and Dengue Hemorrhagic Fever. Clinical Microbiology Reviews. 1998; 11(3):
480-496.
[4] Gibbons RV, Vaughan DW. Dengue an escalating problem. BMJ. 2002; 324: 1563-1566.
[5] World Health Organization, Regional Office for South-East Asia. Dengue/DHF situation of dengue/
dengue haemorrhagic fever in South-East Asia Region 2007. New Delhi: WHO SEARO, 2007. http://
www.searo.who.int/en/Section10/Section332_1098.htm - accessed 11 January 2012.
[6] Aziz MA, Gorham JR, Gregg MB. ‘‘Dacca fever’’ - an outbreak of dengue. Pakis J Med Res. 1967; 6:
83-92.
[7] Russell PK, Buescher EL, McCown JM, Ordonez J. Recovery of dengue viruses from patients during
epidemics in Puerto Rico and East Pakistan. Am J Trop Med Hyg. 1966; 15(4): 573 - 579.
[8] Amin MMM, Hussain AMZ, Murshed M, Chowdhury IA, Mannan S, Chowdhury SA, Banu D. Serodiagnosis of dengue infections by haemagglutination inhibition test (HI) in suspected cases in Chittagong,
Bangladesh. Dengue Bulletin. 1999; 23: 34 – 38.
[9] Hossain MA, Khatun M, Arjumand F, Nisaluk A, Breiman RF. Serologic evidence of dengue infection
before onset of epidemic, Bangladesh. Emerg Infect Dis. 2003; 9(11): 1411-1414.
[10] Podder G, Breiman R, Azim T, Thu MH, Velathanthiri N, Mai LQ, Lowry K, Aaskov JG. Short report:
Origin of dengue type 3 viruses associated with the dengue outbreak in Dhaka, Bangladesh, in 2000
and 2001. Am J Trop Med Hyg. 2006; 74(2): 263-265.
[11] Rahman M, Rahman K, Siddque AK, Shoma S, Kamal AHM, Ali KS, Nisaluk A, Breiman RF. First out
break of dengue hemorrhagic fever, Bangladesh. Emerg Infect Dis. 2002; 8(7): 738-740.
[12] Velathanthiri VGNS, Fernando S, Fernando R, Malavige GN, Peelawaththage M, Jayaratne SD, Aaskov
J. Comparison of serology, virus isolation and RT-PCR in the diagnosis of dengue viral infections in Sri
Lanka. Dengue Bulletin. 2006; 30: 191-196.
[13] World Health Organization. Dengue: guidelines for diagnosis, treatment, prevention and control.
Geneva: WHO. 2009.
91
[14] Innis BL, Nisalak A, Nimmannitya S, Kusalerdchariya S, Chongswasdi V, Suntayakorn S, Puttisri P, Hoke
CH. An enzyme-linked immunosorbent assay to characterize dengue infections where dengue and
Japanese encephalitis co-circulate. Am J Trop Med Hyg. 1989; 40(4): 418-427.
[15] Koraka P, Suharti C, Setiati TE, Mairuhu ATA, Gorp EV, Hack CE, Juffrie M, Sutaryo J, Meer GMVD, Groen
J, Osterhaus ADME. Kinetics of dengue virus-specific serum immunoglobulin classes and subclasses
correlate with clinical outcome of infection. J Clin Microbiol. 2001; 39(12): 4332-4338.
[16] Kao CL, King CC, Chao DY, Wu HL, Chang GJJ. Laboratory diagnosis of dengue virus infection: current
and future perspectives in clinical diagnosis and public health. J Microbiol Immunol Infect. 2005; 38:
5-16.
[17] Chakravarti A, Kumaria R, Berry N, Sharma VK. Serodiagnosis of dengue infection by rapid
immunochromatography test in a hospital setting in Delhi, India, 1999-2001. Dengue Bulletin. 2002;
26: 107-112.
[18] Cuzzubbo AJ, Vaughn DW, Nisalak A, Solomon T, Kalayanarooj S, Aaskov J, Dung NM, Devine PL.
Comparison of Panbio dengue duo enzyme- linked immunosorbent assay (ELISA) and MRL dengue
fever virus immunoglobulin M capture ELISA for diagnosis of dengue virus infection in Southeast Asia.
Clin Diagn Lab Immunol. 1999; 6(5): 705-712.
[19] Nga TTT, Thai KTD, Phuong HL, Giao PT, Hung LQ, Binh TQ, Mai VTC, Nam NV, Vries PJD. Evaluation
of two rapid immunochromatographic assays for diagnosis of dengue among Vietnamese febrile patients.
Clin Vaccine Immunol. 2007; 14(6): 799-801.
[20] Sang CT, Hoon LS, Cuzzubbo A, Devine P. Clinical evaluation of a rapid immunochromatographic test
for the diagnosis of dengue virus infection. Clin Diagn Lab Immunol. 1998; 5(3): 407-409.
[21] Lam SK, Devine PL. Evaluation of capture ELISA and rapid immunochromatographic test for the
determination of IgM and IgG antibodies produced during dengue infection. Clin Diagn Virology.
1998; 10: 75-78.
[22] Vaughn DW, Nisalak A, Solomon T, Kalayanarooj S, Dung NM, Kneen R, Cuzzubbo A, Devine PL.
Rapid serologic diagnosis of dengue virus infection using a commercial capture ELISA that distinguishes
primary and secondary infections. Am J Trop Med Hyg. 1999; 60(4): 693-698.
[23] Vajpayee M, Singh UB, Seth P, Broor S. Comparative evaluation of various commercial assays for
diagnosis of dengue fever. Southeast Asian J Trop Med Public Health. 2001; 32(3): 472-475.
[24] Sang CT, Cuzzubbo AJ, Devine PL. Evaluation of a commercial capture enzyme-linked immunosorbent
assay for detection of immunoglobulin M and G antibodies produced during dengue infection. Clin
Diagn Lab Immunol. 1998; 5(1): 7-10.
[25] Vaughn DW, Green S, Kalayanarooj S, Innis BL, Nimmannitya S, Suntayakorn S, Rothman AL, Ennis
FA, Nisalak A. Dengue in the early febrile phase: Viremia and antibody responses. J Infect Dis. 1997;
176: 322-330.
[26] Vaughn DW, Nisalak A, Kalayanarooj S, Solomon T, Dung NM, Cuzzubbo A, Devine PL. Evaluation of
a rapid immunochromatographic test for diagnosis of dengue virus infection. J Clin Microbiol.1998;
36(1): 234-238.
[27] Miagostovich MP, Nogueira RM, dos Santos FB, Schatzmayr HG, Araujo ES, Vorndam V. Evaluation of
an IgG enzyme-linked immunosorbent assay for dengue diagnosis. J Clin Virol. 1999; 14(3): 183-9.
92
[28] Thaewpia W, Jinathongthai S, Tangthawornchaikul N, Vasanawathana S, Sae-Jang K, Songprakhon P,
Boonprakarn S, Promsorn R, Malasit P. Evaluation of a rapid immunochromatographic test (ICT) for
Dengue IgM and IgG antibodies. Khon Kaen Hosp Med J. 2008; 32: 115-123.
[29] Palmer CJ, King SD, Cuadrado RR, Perez E, Baum M, Ager A. Evaluation of the MRL Diagnostics dengue
fever virus IgM capture ELISA and the Panbio rapid immunochromatographic test for diagnosis of
dengue fever in Jamaica. J Clin Microbiol. 1999; 37(5): 1600-1601.
[30] Yusuf KW, Kausar N, Akbar R, Iqbal N. Comparison of Diagnostic efficacy of rapid diagnostic devices
for Dengue virus infection- a pilot study. J Ayub Med Coll Abbattabad. 2008; 20(4): 26-28.
[31] Cuzzubbo AJ, Endy TP, Nisalak A, Kalayanarooj S, Vaughn DW, Ogata SA, Clements DE, Devine
PL. Use of recombinant envelope proteins for serological diagnosis of dengue virus infection in an
immunochromatographic assay. Clin Diagn Lab Immunol. 2001; 8(6): 1150-1155.
93
A hypothetical intervention to reduce plasma leakage in
dengue haemorrhagic fever
Kolitha H. Sellahewa#
National Hospital of Sri Lanka, Regent’s Street, Colombo 8, Sri Lanka.
Abstract
Plasma leakage from increased vascular permeability, if left unattended, will lead to intravascular
volume depletion. The ensuing tissue hypoperfusion and the consequent life-threatening
complications may have a fatal outcome in dengue haemorrhagic fever (DHF). Although an
accurately calculated volume of fluid infused during the critical phase of plasma leakage can prevent
such an eventuality, the practical difficulties in its execution with properly-timed adjustments to
the fluid infusion rate and the aggressive monitoring needed during this phase of the illness can
limit the expected benefits of an exclusively fluid-based regime. An intervention to reduce plasma
leakage in DHF complementing the standard fluid regime conceivably would improve the outcome.
It is my hypothesis that fresh frozen plasma (FFP) by Fc receptor blockade and the associated
reduction in immune-enhanced viral replication could reduce cytokine-mediated increase in
vascular permeability. Additionally, albumin in FFP, by adhering to the glycocalyx, could further
compromise fluid fluxes during the critical phase of DHF. However, this hypothesis needs to be
tested by a randomized controlled study.
Keywords: Dengue haemorrhagic fever; Reduced plasma leakage; Intervention with fresh frozen plasma.
Introduction
The pathophysiological hallmark in dengue haemorrhagic fever (DHF) is plasma leakage.
All the life-threatening complications of DHF ranging from shock, severe gastrointestinal
bleeding, disseminated intravascular coagulation, hepatic failure and encephalopathy are
a consequence of compromised tissue perfusion stemming from plasma leakage and the
attendant intravascular volume depletion.[1] Clinical management of DHF centres around the
judicious use of intravenous fluids to match the plasma leakage during this critical phase of
DHF, which lasts about 24 to 48 hours, and thereby prevent the life-threatening and often
fatal adverse consequences of prolonged shock. The collective experience of clinicians
managing patients with dengue globally, and in Thailand in particular, has refined fluid
#
94
Intervention to reduce plasma leakage in dengue haemorrhagic fever
therapy with precise prescriptions of a fluid quota for this critical period of plasma leakage.
The development and application of new national guidelines on the management of dengue
fever (DF) and DHF by the Epidemiology Unit of the Ministry of Health, Sri Lanka, which
has used inputs and expertise from a wide variety of sources, has facilitated the management
of DHF.[2]
Fluid therapy in the presence of plasma leakage
The predictable benefits and prevention of morbidity and mortality due to DHF by the
application of this management approach require early detection of entry into the critical
phase, close monitoring during the entire phase of plasma leakage, subtle adjustments to the
fluid infusion rates, and an informed choice between crystalloids (isotonic saline) and colloids
(Dextran 40 and Hetastarch). For optimal benefit, such adjustments need to be correlated
with the precise phase of plasma leakage to suit individual patient needs and the dynamism
of plasma leakage.[2] For instance, while Dextran 40 would be the colloid of choice when
plasma leakage is at its peak, it could have an adverse impact when given towards the end
of the critical phase of plasma leakage, at which stage, Hetastarch would be a better choice
if a colloid is required. Dextran 40, by volume expansion, could cause fluid overloading if
given towards the end of the critical phase when cessation of plasma leakage is imminent
and the leaked-out fluid is getting reabsorbed. A prerequisite for the success of this therapy
is the ability to detect early the entry of the patient into the critical phase of plasma leakage.
This can be a challenging proposition in busy and overcrowded conditions prevailing in most
developing countries, with the incidence of febrile illnesses due to a variety of causes other
than dengue. Under these conditions, it is possible to falter in the critical monitoring needed
to detect plasma leakage as well as apply flexibility to the fluid regime to match the dynamics
of fluid leakage. In this context, an intervention to reduce plasma leakage to complement
fluid therapy could offset the inherent drawbacks of a single modality of intervention and
thwart the advent of life-threatening complications of DHF, particularly during epidemics
that can overwhelm resource limitations.
Plasma leakage in DHF
Corticosteroids have been used to reduce plasma leakage, but there is inadequate evidence
to support its use for this purpose.[3,4,5,6] In my search for an interventional option, I have
conceptualized the use of fresh frozen plasma (FFP) to reduce plasma leakage in DHF. Plasma
leakage is the result of increased vascular permeability brought about by a cytokine storm
without any vascular damage or inflammation.[1,6,7,8] The quantum of cytokine production
and, hence, the magnitude of plasma leakage is directly related to the viral load. Antibodyenhanced viral replication is a well recognized mechanism implicated in increasing the viral
load.[1,6,9] Immunoglobulins in FFP by Fc receptor blockade could compromise antibody
enhanced viral replication by preventing the uptake by macrophages of dengue viruses
95
complexed with non-neutralizing, cross-reactive, dengue-specific antibodies. Even though
intravenous immunoglobulin has been used in dengue, it has been used late in the disease
course on patients already in shock and there are no good randomized controlled trials (RCT)
to date that have tested its efficacy when given early at the inception of plasma leakage.[10]
The basic Starling principle still holds true in explaining microvascular ultrafiltration based on
the balance of the oncotic and hydrostatic pressures; but the glycocalyx, which is a gelatinous
layer lining the inner surface of the vascular endothelium, is also implicated in controlling the
fluid flow across the endothelium.[7,8,9] Plasma proteins, particularly albumin, adsorb to the
positively-charged residues in the glycocalyx and restrict ultrafiltration.[11,12,13,14,15] Albumin
in FFP, by adhering to the glycocalyx, could reduce the transfer of fluid across the vascular
membrane. However, the beneficial effect of albumin in dengue, if any, could be evident
only early in the disease course before shock, as in severe disease, albumin too leaks out of
the vascular compartment. It is hypothesized therefore that when given early, FFP, by these
two independent mechanisms, could reduce fluid fluxes across the vascular membrane in
patients with DHF.
In a previous study designed to test the effect of FFP on thrombocytopenia in DHF, I made
an incidental observation of a drop in the haematocrit (HCT) in the treatment arm of the
randomized control trial (RCT), which was not evident in the control arm that received only
isotonic saline, implying fluid retention in the face of increased vascular permeability in the
group of patients who received FFP.[16] J.S.D.K. Weeraman and I have carried out in-depth
reviews into deaths related to dengue as well as random audits on the clinical management
of DF and DHF from 1 September 2010 to 31 January 2011. These audits and reviews were
done in state sector hospitals in the western, north western, central, north central, northern,
Sabaragamuwa and the southern provinces in Sri Lanka, including the National Hospital of
Sri Lanka, the Lady Ridgeway hospital for children, as well as a private hospital in Colombo.
Out of a total of 34 patients on whom death reviews were done, 11 had received FFP. Out of
a total of 45 patients on whom clinical audits were done, 12 had received FFP. We observed
a drop in the haematocrit in 20 out of the total of 23 patients with DHF who had received
FFP during the course of their management. Out of the 20 patients in whom the haematocrit
dropped, four patients had overt gastrointestinal bleeding and all of them died. Seven out
of the 20 patients in whom the HCT dropped were fluid overloaded, two of whom died.
It is possible that bleeding as well as fluid overload could have contributed to the observed
drop in the HCT among some (11 out of 20) of these audited patients. Whether FFP was a
contributory factor to the drop in HCT by an independent mechanism, as hypothesized in
this cohort, is conjectural. Nevertheless, all these incidental observations of a drop in the
HCT in patients who had received FFP tend to support the hypothesized benefits of FFP
used early in the critical phase in DHF. However, there are limitations in the interpretation
of the drop in HCT among some of the patients in the audited cohort as blood loss and
fluid overload could have been contributory factors other than the hypothesized reduction
in plasma leakage. Before advocating the use of FFP as an intervention to reduce plasma
leakage in DHF, it would be necessary to test this hypothesis by a RCT which I have designed
but is awaiting ethical clearance for execution.
96
Discussion
An intervention to reduce the leakage of fluid out of the vascular compartment during the
critical phase of plasma leakage in DHF could add a new dimension to the management
of patients with DHF. I believe that a critically-timed dose of FFP in selected patients with
DHF could effect a reduction in the morbidity and mortality due to DHF. It is based on my
conceptualized hypothesis as well as personal experience in making incidental observations
on DHF patients who had received FFP. This could be a major advance in the management
of DHF as it utilizes an easily implementable and readily available intervention targeting
an area of critical importance in the pathogenesis of a disease spreading globally, for which
there is no specific therapeutic option available to date.
Until such time as we can complete our investigations, I can only advocate strict and
diligent adherence to fluid therapy as detailed in the Sri Lankan national guidelines on the
management of DF and DHF which have international applicability.
Acknowledgements
I am thankful to Dr N. Samaraweera and Dr C.A. Wanigathunga for helping me with the
literature reviews on this subject and the development of the research protocol for the planned
RCT. I am grateful to Dr Paba Palihawadana, Dr Sudath Peiris, Dr J.S.D.K. Weeraman and
Dr Hasitha Tissera of the Epidemiology Unit of the Ministry of Health, Sri Lanka, for assistance
in carrying out the death reviews and clinical audits. I also appreciate the cooperation and
assistance provided by the directors, medical superintendents, doctors and nurses in the
hospitals where these audits and death reviews were done. I appreciate with gratitude the
valuable comments made by Professor Colvin Goonaratna on this article.
References
[1] Srikiatkhachorn A. Plasma leakage in dengue haemorrhagic fever. Thromb Haemost. 2009; 102(6):
1042-9.
[2] Sri Lanka. National guidelines on management of dengue fever & dengue haemorrhagic fever in adults.
Colombo: Ministry of Health, 2010.
[3] Rajapakse S. Corticosteroids in the treatment of dengue illness. Trans R Soc Trop Med Hyg. 2009;
103(2): 122-6.
[4] Rajapakse S. Intravenous immunoglobulins in the treatment of dengue illness. Trans R Soc Trop Med
Hyg. 2009; 103(9): 867-70.
[5] Tassniyom S, Vasanawathana S, Chirawatkul A, Rojanasuphot S. Failure of high-dose methylprednisolone
in established dengue shock syndrome: a placebo-controlled, double-blind study. Pediatrics. 1993;
92(1): 111-5.
97
[6] Sumarmo, Talogo W, Asrin A, Isnuhandojo B, Sahudi A. Failure of hydrocortisone to affect outcome in
dengue shock syndrome. Pediatrics. 1982; 69(1): 45-9.
[7] Libraty DH, Endy TP, Houng HS, Green S, Kalayanarooj S, Suntayakorn S, Chansiriwongs W, Vaughn
DW, Nisalak A, Ennis FA, Rothman AL. Differing influence of virus burden and immune activation on
disease severity in secondary dengue -3 virus infections. J Infect Dis. 2002; 185(9): 1213-21.
[8] Avirutnan P, Malasit P, Seliger B, Bhakdi S, Husmann M. Dengue virus infection of human endothelial
cells leads to chemokine production, complement activation, and apoptosis. J Immunol. 1998; 161(11):
6338-46.
[9] Vaughn DW, Green S, Kalayanarooj S, Innis BL, Nimmannitya S, Suntayakorn S, Endy TP, Raengsakulrach
B, Rothman AL, Ennis FA, Nisalak A. Dengue viraemia titre, antibody response pattern, and virus
serotype correlate with disease severity. J Infect Dis. 2000; 181(1): 2-9.
[10] Duchini A, Govindarajan S, Santucci M, Zampi G, Hofman FM. Effects of tumor necrosis factor-alpha
and interleukin-6 on fluid-phase permeability and ammonia diffusion in CNS-derived endothelial cells.
J Invest Med. 1996; 44(8): 474-82.
[11] Reitsma S, Slaaf DW, Vink H, van Zandvoort MA, oude Egbrink MG. The endothelial glycocalyx:
composition, functions,and visualization. Pflugers Arch. 2007; 454(3): 345-59.
[12] Wills BA, Nguyen MD, Ha TL, Dong TH, Tran TN, Le TT, Tran VD, Nguyen TH, Nguyen VC, Stepniewska
K, White NJ, Farrar JJ. Comparison of three fluid solutions for resuscitation in dengue shock syndrome.
N Engl J Med. 2005; 353(9): 877-89.
[13] Michel CC, Curry FE. Microvascular permeability. Physiol Rev. 1999; 79(3): 703-61.
[14] Huxley VH, Curry FE. Differential actions of albumin and plasma on capillary solute permeability. Am
J Physiol. 1991; 260(5 Pt 2): H1645-54.
[15] Wills BA, Oragui EE, Dung NM, Loan HT, Chau NV, Farrar JJ, Levin M. Size and charge characteristics
of the protein leak in dengue shock syndrome. J Infect Dis. 2004; 190(4): 810-8.
[16] Sellahewa KH, Samaraweera N, Thusita KP, Fernando JL. Is fresh frozen plasma effective for
thrombocytopenia in adults with Dengue fever. Ceylon Med J. 2008; 53(2): 36-40.
98
Entomological investigations of dengue vectors in
epidemic-prone districts of Pakistan during 2006–2010
Muhammad Mukhtar,a# Zarfishan Tahir,b Taj Muhammad Baloch,c
Faisal Mansoord & Jaleel Kamrane
Department of Zoonotic and Vector-Borne Diseases, Public Health Laboratories Division, National
Institute of Health, Islamabad, Pakistan.
a
Bectoriologist Laboratory, Institute of Public Health, 6-Abdul Rehman Choughtai Road, Lahore,
Pakistan.
b
Directorate of Malaria Control, Wahadat Colony, Hyderabad, Pakistan.
c
d
Pakistan Medical Research Council, Islamabad, Pakistan.
Epidemic Investigation Cell, National Institute of Health, Islamabad, Pakistan.
e
Abstract
Intensive entomological investigations were carried out in seven dengue epidemic-prone districts
of Pakistan, classifying them into three geographical regions, viz. southern, central and northern
Pakistan. A total of 5132 water habitats from 2136 households in and around dengue-positive
houses were sampled. Additionally, 264 samples each at least 30 metres away from dengue-positive
houses were also collected from outdoor habitats. Only indoor samples data were used for the
estimation of entomological indices.
House Index, Container Index and Breteau Index were estimated at 39.42%, 27.96% and 67.20
respectively. Underground water tanks showed the highest (42.38%) positivity, followed by earthen
pots (36.97%), drums (33.38%) and the least (4.58%) from discarded containers. From outdoor
sites, only 5.05% (n=14) samples were found positive. Aedes aegypti and Aedes albopictus species
exhibited a distinct association with different geographical regions. In the south of the country only
Ae. aegypti was recorded in all (n=452) positive habitats while in the central part, both Ae. aegypti
and Ae. albopictus were reported from 88.2% (n=253) and 11.8% (n=34) of the total 287 positive
habitats respectively. In the north/submountainous region, 88.45% (n=628) of 710 positive samples
were found infested with Ae. albopictus. Both species showed a significant population-rising trend
from September to November, similar to the dengue case-load trend.
Keywords: Entomological investigations; Aedes aegypti; Aedes albopictus; Dengue; Pakistan; 2006-2010.
#
99
Entomological investigations of dengue vectors in Pakistan
Introduction
Dengue fever (DF) and dengue haemorrhagic fever (DHF) are considered important reemerging arboviral diseases in more than 100 tropical and subtropical countries of the world.[1]
The disease epidemiology is complex in nature and requires understanding of a variety of
factors that include weather and environmental changes,[2,3,4] vector species composition and
behaviour,[5,6,7] population dynamics and degree of immunity in local population.[8,9,10]
In Pakistan, dengue is emerging as one of the major public health problems, particularly
since 2005, threatening the lives of millions of people due to prevailing peculiar socioeconomic
conditions and epidemiological situation. Historically, dengue has been endemic in the
southern parts of the country. In Pakistan, dengue was recognized for the first time in 1994
in Karachi and one patient out of 145 cases died.[11] In October 1995, 57 out of 76 persons
were found positive for antibodies against the dengue virus in Hub, southern Balochistan. In
October 2003, dengue outbreaks were detected for the first time in submountainous areas
of Haripur district, Khyber Pakhtoonkhawa province and Khushab district, Punjab province,
claiming six lives among 717 cases. In October 2005, dengue hit Karachi again after 10
years and 21 deaths out of the total 103 confirmed cases were recorded.[12,13] Since then,
the disease has become widely prevalent and has been accepted as one of the major public
health problems in Pakistan. Until 2010, 26 270 cases and 156 deaths have been reported
(Epidemic Investigation Cell, National Institute of Health, 2010 Unpublished data).
Aedes aegypti and Aedes albopictus have been considered as the major vectors of dengue
in South-East Asia, including Pakistan.[14,15,16] Both species have been closely associated with
human dwellings due to their breeding preference for clean-water domestic habitats.[17,18]
Entomological surveillance, particularly based on larval surveys, provides vital information for
better dengue disease management. However, in Pakistan, at present there is no systematic
entomological surveillance system, particularly after the 1980s to update the knowledge of
vector species and their bionomics.
In view of the deteriorating situation with regard to dengue/DHF in the country and poor
knowledge of vector(s), systematic and intensive entomological surveys were conducted in
seven high-risk districts during dengue outbreaks to identify the potential breeding sites of
dengue vector(s) and to determine the levels of vector infestations at each affected area by
using the commonly used larval indices (House, Container and Breteau). Finally, in order to
estimate the transmission potential for dengue outbreaks in the country, the new knowledge
generated through these investigations will provide a technical basis to design evidencebased, community-friendly and sustainable preventive and control measures against dengue
in Pakistan.
100
Study type and selection of study areas
The study was descriptive in nature and all seven dengue epidemic-prone districts in the
country were selected for entomological surveys and were classified into three geographical
areas, viz. Southern (Karachi), Central plain (Lahore), and Northern/submountainous areas
(Rawalpindi, Islamabad, Attock, Chakwal and Haripur). Detail of descriptions of selected
districts are given in Figure 1 and Table 1.
Figure 1: Dengue epidemic-prone districts in Pakistan
101
102
Southern
Central
Northern
(Submountain)
Northern
(Submountain)
Northern
(Submountain)
Northern
(Submountain)
Northern
(Submountain)
Lahore
Attock
Rawalpindi
Islamabad
Haripur
Chakwal
Geographic
region
Karachi
District
32-93
34-22
33-72
33-60
33-78
31-56
24-86
Lat (N)
72-85
73-15
73-06
73-04
72-36
74-35
67-02
Long
(E)
Geography
201
610
585
560
560
217
24
Elev
(m)
30.6
22.8
28.6
28.6
30.14
30.8
30.7
Temp C
(Max)
16.4
11.4
14.1
14.1
15.5
17.8
21.5
(Temp)
Min
56.2
56.0
56.6
55.8
57.6
54.7
68.7
R/H (%)
Meteorology
853
680
1450
1364
783
729
217
Ppt
(mm)
6524
1725
906
5286
6857
1772
3527
Total
96
88
167
213
95
653
715
Urban
Area (sq km)
6428
1637
739
5073
6762
1119
2812
Rural
1.37
0.89
1.12
4.5
1.66
9.5
14.99
Total
(m)
21.7
12.0
87.7
50.3
19.7
81.2
94.8
Urban
(%)
78.3
88.0
12.3
49.7
80.3
18.8
5.3
Rural
(%)
Population (2010)
Table 1: Description of all dengue epidemic-prone districts of Pakistan
210
516
1236
851
186
5380
4250
Total
3097
1214
5882
10 627
3442
11 854
19 864
Urban
167
478
186
155
197
1,604
280
Rural
Density (Pop/sq km)
Population estimation
The population in 2010 and other characteristics of the selected districts have been calculated
on the basis of the estimation provided by the Population Census Organization and the
Federal Bureau of Statistics, Government of Pakistan.[19,20]
Sampling strategies
In each selected district, maps of dengue cases were prepared and most-affected Union
Councils (basic administrative unit/area in the country) were identified for entomological
investigations. The basic sampling unit was the household and at least 10 households around
each selected dengue case were searched for water-holding containers as possible breeding
sites. All indoor habitats were classified into underground cemented water tanks, overhead
water tanks, earthen pots, discarded containers and drums.
Additionally, some potential outdoor breeding sites which include open ponds (including
street pools, drains, irrigated fields, etc.) and used tyres, at least 30 metres away from
patients’ homes, were also included in the surveys. These habitats were examined during
an outbreak for the presence of Aedes larvae using larval net or dipper. Collected specimens
were preserved in 70% formalin for species identification in laboratory using Leopoldo (2004)
key.[21] To estimate the entomological indices (House Index (HI), Container Index (CI), and
Breteau Index (BI)), only the data of indoor entomological surveys was used. Outdoor surveys
data were used only as a reference to compare the breeding preferences of Aedes species
between outdoor and indoor habitats.
Results
On an average, the highest number of water-holding containers in each household were
found in Karachi (n=3.0), followed by Rawalpindi (n=2.6) and Attock (n=2.5). Out of the
total 2136 households surveyed, 23.36% (n=499) and 19.10% (n=408) were in Karachi and
Lahore respectively. The least number of households were surveyed in Chakwal (7.82%) and
Attock (8.80%). Of the total households surveyed, 39.42% (n=842) were found positive for
Ae. aegypti and Ae. albopictus; the highest HI was found in Karachi (46.5%), followed by
Haripur (42.0%), Lahore (41.7%) and Islamabad (41.4%). Of the total 5132 indoor samples
collected, 29.17% (n=1497) and 15.90% (n=816) were collected in Karachi and Lahore
respectively, of which 27.96% (n=1435) were found positive with Aedes species. The highest
CI was observed in Lahore (34.6%), followed by Karachi (30.2%) and Islamabad (29.9%).
The highest BI was recorded in Karachi (90.6), followed by Lahore (69.1) and Islamabad
(65.8). Overall, the HI, CI and BI of the seven districts were estimated at 39.42%, 27.96%
and 67.2 respectively. Details of the households sampled, and the HI, CI and BI are given
in Table 2.
103
Table 2: District-wise details of number of households, average number of containers,
positivity rate, HI, CI, and BI
House Index (HI)
District
Province
Total
HH
Container Index (CI)
Positive
Index
(%)
Av. no of
containers
Containers
inspected
Positive
Index
(%)
Breteau
Index
(BI)
Karachi
Sindh
499
232
46.5
3.0
1497
452
30.2
90.6
Lahore
Punjab
408
170
41.7
2.0
816
282
34.6
69.1
Attock
Punjab
188
54
28.7
2.5
470
79
16.8
42.0
Rawalpindi
Punjab
291
95
32.6
2.6
757
184
24.3
63.2
Islamabad
Capital Territory
295
122
41.4
2.2
649
194
29.9
65.8
Haripur
K. Pakhtoonkhawa
288
121
42.0
2.0
576
166
28.8
57.6
Chakwal
Punjab
167
48
28.7
2.2
367
78
21.2
46.7
2136
842
39.42
5132
1435
27.96
67.2
Total
Among the indoor water-holding containers, underground cemented water tanks showed
the highest positivity rate (42.38%), followed by earthen pots (36.97%) and drums (33.38%).
Only 4.58% (n=16) samples from discarded containers were found positive. However, no
sample from overhead water tanks was found positive. Among the outdoor breeding sites,
only 5.30% (n=14) of the total 264 samples were found positive, of which all were from
used tyres and no sample from open ponds was found positive with Aedes species. Details
of the district-wise samples collected and the positivity rate are given in Table 3.
In the southern part of the country (Karachi), all (n=452) indoor positive samples were
positive only with Ae. aegypti and no Ae. albopictus positive sample was recorded. However,
in central plains (Lahore), 89.7% (n=253) and 10.3% (n=34) of the positive samples were
positive with Ae. aegypti and Ae. albopictus respectively. In the northern/submountainous
areas (Haripur, Rawalpindi, Islamabad and Attock), 93.4% (n=158), 89.1% (n=169), 87.1%
(n=170) and 86.1% (n=68) respectively were found positive with Ae. albopictus and the
rest were positive with Ae. aegypti. From the outdoor collections, all (n=14) samples were
positive with only Ae. albopictus. District-wise details of the association of Ae. aegypti
and Ae. albopictus with individual habitat under different geographical areas are given in
Table 4.
Among the 1435 indoor positive water containers, 84.88% (n=1218) were found
uncovered or poorly covered at the time of sample collection. However, only 15.12% (n=217)
habitats which were covered properly were found positive. Details of the correlation between
the sample positivity rate and covering of water containers are given in Table 5.
104
432
115
62
122
158
126
35
1050
Karachi
Lahore
Attock
Rawalpindi
Islamabad
Haripur
Chakwal
Total
445
15
61
68
43
24
43
191
42.38
42.9
48.4
43.0
35.2
38.7
37.4
44.2
960
84
112
145
154
97
143
225
0
0
0
0
0
0
0
0
+ve
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
%
Total
%
Total
+ve
Overhead water tank
Underground water
tank
1426
124
145
154
219
127
274
383
Total
476
36
36
68
64
23
125
124
+ve
Drum
33.38
29.0
24.8
44.2
29.2
18.1
45.6
32.4
%
1347
112
172
144
198
166
219
336
Total
498
27
69
54
72
32
109
135
+ve
Earthen pot
Indoor breeding sites
36.97
24.1
40.1
37.5
36.4
19.3
49.8
40.2
%
349
12
21
48
64
18
65
121
Total
16
0
0
4
5
0
5
2
+ve
4.58
0.0
0.0
11.1
8.0
0.0
7.7
1.7
%
Discarded container
5132
367
576
649
757
470
816
1497
1435
78
166
194
184
79
282
452
Sub total
27.96
21.3
28.8
29.9
24.3
16.8
34.6
30.2
155
5
18
13
31
0
47
41
Total
14
0
3
1
5
0
5
0
+ve
Used tyre
9.03
0.0
16.7
7.7
16.1
0.0
10.6
0.0
%
109
9
15
15
17
11
26
16
Total
0
0
0
0
0
0
0
0
+ve
Open pond
Outdoor breeding sites
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
%
5396
381
609
677
805
481
889
1554
1449
78
169
195
189
79
287
452
Grand total
26.85
21.3
28.8
29.9
24.2
16.9
34.7
30.5
Table 3: District-wise number of samples collected and positivity rate of water containers with Aedes species in Pakistan
105
106
191
38
7
6
7
2
4
255
Karachi
Lahore
Attock
Rawalpindi
Islamabad
Haripur
Chakwal
Total
190
11
59
61
37
17
5
0
445
15
61
68
43
24
43
191
0
0
0
0
0
0
0
0
A. ag
0
0
0
0
0
0
0
0
A. alb
0
0
0
0
0
0
0
0
T
A. alb
T
A. ag
Overhead water tank
Underground water tank
268
4
4
11
7
2
116
124
A. ag
208
32
32
57
57
21
9
0
A. alb
Drum
476
36
36
68
64
23
125
124
T
262
7
5
7
7
2
99
135
A. ag
236
20
64
47
65
30
10
0
A. alb
Earthen pots
498
27
69
54
72
32
109
135
T
2
0
0
0
0
0
0
2
A. ag
14
0
0
4
5
0
5
0
A. alb
16
0
0
4
5
0
5
2
T
Discarded containers
787
15
11
25
20
11
253
452
A. ag
648
63
155
169
164
68
29
0
A. alb
Total
1435
78
166
194
184
79
282
452
T
0
0
0
0
0
0
0
0
A. ag
14
0
3
1
5
0
5
0
A. alb
Used tyres
14
0
3
1
5
0
5
0
T
0
0
0
0
0
0
0
0
A. ag
0
0
0
0
0
0
0
0
A. alb
Open ponds
0
0
0
0
0
0
0
0
T
787
15
11
25
20
11
253
452
A. ag
Table 4: District-wise number of positive containers with Aedes aegypti and A. albopictus in Pakistan
662
63
158
170
169
68
34
0
A. alb
Grand total
1449
78
169
195
189
79
287
452
T
31
5
4
3
2
7
3
55
12.4
Karachi
Lahore
Attock
Rawalpindi
Islamabad
Haripur
Chakwal
Totals
Percentages
83.1
370
12
50
61
36
20
36
155
Poorly
4.5
20
0
4
5
4
0
2
5
Properly
0
0
0
0
0
0
0
0
0
Un
0
0
0
0
0
0
0
0
0
Poorly
0
0
0
0
0
0
0
0
0
Properly
Coveredness
Coveredness
Un
Overhead Water Tanks
Underground Water Tanks
22.5
107
12
18
10
16
8
21
22
Un
71.8
342
21
13
53
44
15
101
95
5.7
27
3
5
5
4
0
3
7
Poorly Properly
Coveredness
Drums
13.7
68
3
9
7
9
5
16
19
Un
52.2
260
11
36
19
37
12
59
86
34.1
170
13
24
28
26
15
34
30
Poorly Properly
Coveredness
Earthen Pots
100
16
0
0
4
5
0
5
2
Un
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Poorly Properly
Coveredness
Discarded Containers
17.1
246
18
34
23
33
17
47
74
Un
67.7
972
44
99
133
117
47
196
336
15.1
217
16
33
38
34
15
39
42
Poorly Properly
Coveredness
Total
100
14
0
5
4
0
0
5
0
Un
Coveredness
Open Ponds
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Poorly Properly Un Poorly Properly
Coveredness
Used Tyres
Table 5: Association between covering of containers and positivity with Aedes species in Pakistan
17.9
260
18
39
27
33
17
52
74
Un
67.1
972
44
99
133
117
47
196
336
15.0
217
16
33
38
34
15
39
42
Poorly Properly
Coveredness
Grand Totals
107
Out of the total 1449 indoor and outdoor positive samples, 35.5% (n=524) were found
positive during the month of November, followed by 34.3% (n=434) and 27.3% (n=277)
in October and September respectively. Very low vector densities were recorded during the
cold (December–February) and hot months (May–July). Among the districts, there was no
notable difference in the population-building trend of both vector species (data not shown).
Month-wise, the case-load in the entire country during the study period also exhibited the
same rising trend, and 96.00% (n=13 925) of the total dengue cases and 96.79% (n=151)
deaths due to dengue were reported during September–November (Table 6).
Discussion
The occurrence of mosquito immatures in different habitats reflects both oviposition
preference of females as well as the ability of the immatures to survive in a particular
habitat. Changes in the physio-chemical and biotic characteristics of the habitat may create
conditions either favourable or unfavourable for their breeding success, depending upon the
Table 6: Month-wise details of case-load, deaths and number of
containers examined and positivity rate
Dengue cases (2006–2010)
Entomological investigations
Suspected
Confirmed
%age
Death
Containers
examined
Positive
%age
January
188
9
0.06
0
100
0
0.0
February
134
0
0.00
0
97
0
0.0
March
45
0
0.00
0
121
21
17.4
April
129
11
0.08
0
156
39
25.0
May
23
0
0.00
0
90
23
25.6
June
67
0
0.00
0
107
0
0.0
July
787
22
0.15
0
145
15
10.3
August
1891
412
2.84
0
499
66
13.2
September
4781
2543
17.53
26
1015
277
27.3
October
7418
4671
32.20
49
1267
434
34.3
November
9986
6711
46.27
76
1477
524
35.5
December
821
126
0.87
5
322
45
14.0
26 270
14 505
156
5396
1449
Total
108
range of tolerance of different species.[22,23] The present investigations explain the breeding
preference of Ae. aegypti and Ae. albopictus to different water-holding containers in different
geographical regions.
In South-East Asia, both these species are important vectors of dengue and dengue
haemorrhagic fever and, traditionally, both species, particularly Ae. aegypti, are believed
to be associated with man-made artificial habitats in shaded places in human dwellings.
[14,17,18]
Our results confirm these associations as 100% positive habitats were man-made and
domestic in nature. In Thailand, a distinct endophilic behaviour of Ae. aegypti and exophilic
behaviour of Ae. albopictus were recorded.[16,24] Present investigations also support the
indoor preference of Ae. aegypti. Similarly, Chen et al (2006)[25] and Sulaiman et al (1991)[26]
reported a dominant endophilic behaviour of Ae. albopictus in addition to outdoor breeding
preferences in Malaysia. Our finding also supported these findings. Furthermore, we, in
agreement with other researchers,[17,24,27,28,29] confirm that the most attractive indoor breeding
sites of Ae. aegypti and Ae. albopictus and their sequence was underground cemented water
tanks, earthen pots and drums (Figure 2). Normally, a underground cemented water tank
(Figure 2a) is 8’x10’ in size having 8–12 feet depth and is in common use in these districts,
and we observed that these tanks were never emptied completely and cleaned ever since
their construction. Most people make a small hole in their metallic lid to insert a pipe for
filling and taking out water, which makes an easy access of Aedes mosquitoes to the water
for breeding.
The use of narrow-neck earthen pots (Figure 2b) is also very common for water storing
and these pots are mainly used in rural communities for drinking purposes and are kept in
shaded places with extreme care taken to cover them. However, we observed that refrigerators
were in common use even among poor communities which greatly reduced the use of these
earthen pots for drinking water storage, but more for general domestic use. In northern parts
of Pakistan, particularly in Haripur and Chakwal districts, we observed a common use of a
very particular type of wide-neck earthen pot (Figure 2c) which is 3.5–4.0 feet tall and 23–25
kg in weight, having a storage capacity of 60–70 litres of water. However, these pots are
Figure 2: Different water-holding containers and their physical conditions
at the time of sampling
Figure 2a:
Underground
water tanks
Figure 2b:
Narrow-neck
earthen pots
Figure 2c:
Wide-neck
earthen pots
Figure 2d:
Drums
Figure 2e:
Overhead
water tanks
109
usually covered with a very poorly maintained lid made of wood. To keep the water cool,
these pots are kept dug in the ground up to half of their height. All these characteristics and
household habits make it almost impossible to wash and clean them properly, which results
in profound breeding of Aedes mosquitoes.
Despite the large number of samples that were collected, we did not find any positivity
in the overhead water tanks (Figure 2e), which are mainly made of plastic and are placed in
open sunlight on the roofs of houses. The use of these tanks has become very common in the
country due to rapid urbanization, particularly since the late 1980s. During the sampling we
also observed that these tanks were properly covered and there was a high temperature inside
due to their location in open sunlight, which most probably prevents the Aedes mosquito
from breeding while other water containers in the same household placed in shaded places
were found positive. These findings further confirm the breeding preferences of both the
Aedes species for shaded indoor habitats.
In contrast with some previous findings,[30,31,32] interestingly, our investigations indicated
a distinct negative association of Ae. aegypti particularly, and Ae. albopictus generally, with
used tyres and discarded containers. Out of the 349 samples from discarded containers, only
2 and 14 containers were found positive with Ae. aegypti and Ae. albopictus respectively.
However, we could not find any association of Ae. aegypti with used tyres.
In disagreement with Cruz et al (2008),[30] and in agreement with Kittayapong et al
(2006),[33] our investigations revealed that proper covering of water-holding containers
make a direct impact on the reduction in the densities of both species. However, the use
of larvicides in these habitats should also be a top most priority for better management of
dengue vectors.
During our interviews with the sampled households, we noticed that most of them
did not know about the breeding of mosquitoes inside these water-holding containers and
they had no idea about their control through washing, cleaning or proper covering of these
containers and through the use of chemicals. We also noticed that due to the uncertainty of
water supply, communities did not remove even small quantities of the water remaining in
these containers before refilling them when there was water again; so, this remaining water
contained eggs, larvae and pupae. Since Aedes mosquitoes require only a small quantity
of water for breeding, once a water container becomes infected with Aedes mosquitoes,
it remains infected till complete emptying and proper washing. Similarly, Aedes eggs can
also stick to the coarse walls of these containers even when there is no or little water, and
these eggs hatch later after refilling and, most probably, due to this reason, some covered
containers were also found positive at the time of sampling. These findings further indicate
the need of use of larvicides for proper control of dengue vectors breeding in these manmade habitats.
110
Some researchers have reported the influence of some life-limiting factors of latitude,
altitude, temperature, rainfall, humidity, etc., on the geographical distribution and densities
of Aedes species.[4,34,35,36] Consistent with these findings we also recorded a discernible
demarcation in the occurrence of both species in different geographical areas of Pakistan.
In Karachi (southern area), which is located at 24 metres above sea level, only Ae. aegypti
was the prevalent species whereas in the northern/submountainous areas (500–600 metres
above sea level with upper limit of 2500 metres), Ae. albopictus showed a significant
dominance. However, in the central part of the country, Ae. aegypti showed a dominance
while Ae. albopictus also showed reasonably high densities. In India, Ae. aegypti has been
recorded in 1968 at an altitude of 2500 metres above sea level at Mcleodganj, western
Himalayas.[37] In Pakistan, the submountainous areas are mostly covered with thick vegetation,
while in Lahore, there is also a very large area covered by the Changa Manga National Forest
Park. Chen et al (2006)[25] and Aslam Khan and Sulman (1969)[38] also reported a significant
association of Ae. albopictus with thickly vegetated areas.
Similar to the malaria vectors in Pakistan, overall, both the Aedes species exhibited a
well-defined rising trend in their population in the post-monsoon season (September to
November) in all selected areas. Li et al (1985)[39] revealed a positive correlation between a
dengue outbreak and rainfall due to increased number of breeding habitats of Aedes vectors
in Malaysia. However, we noticed that none of the indoor positive breeding habitats has
any direct link with rainwater. In our study areas, particularly in Karachi, the water supply
is very erratic, irregular and it is available for a very short period of 60–90 minutes in a
day without any fixed timings (sometimes on alternate days). Therefore, water has to be
stored in drums, buckets, underground tanks, earthen pots, etc. All positive samples were
collected from these water containers placed inside the houses. Similarly, the average rainfall
in Karachi is also very low and the water pools in the streets become organically polluted
and support the breeding of only Culex mosquitoes. Though in the submountainous region,
the annual rainfall is high, even then all samples collected from the open-field habitats,
including rainwater pools, were found negative, while all positive habitats were man-made
inside the houses which have no link with rainwater. These findings indicate that there is
no correlation between rain and number of Aedes breeding sites in Pakistan. However, the
month-wise data of dengue cases showed a strikingly rising trend after the monsoon months
(September–November) parallel to the vector density data. During the study period, 95.53%
of the dengue case-load was reported during these months, and there was a rapid decline
in the cases during and after December, which indicated a positive correlation between the
vector densities and the disease incidence.
Our investigations reported high levels of HI, CI and BI. The high BI revealed a significant
direct relationship between positive containers and houses and confirms a high transmission
potential for dengue outbreaks in the study districts.[6,31] A very high dengue case-load in the
selected districts (>80% of total case-load of the county) further confirms our findings.
111
Conclusions and recommendations
The present five-year entomological investigations of the dengue outbreaks during 2006–2010
showed a distinctly high level of vector(s) infestation in the man-made shaded habitats
in human dwellings in the districts covered by our study, particularly during September–
November, in parallel with the disease trends.
Since there is a rising incidence of dengue/DHF in Pakistan, particularly since 2005,
there is an urgent need: (i) to establish a separate “Dengue Control Cell” within the Ministry
of Health as part of overall health system strengthening; (ii) for a mass health information
and promotion campaign for the sensitization of local communities for better acceptance
of intervention(s), particularly the use of personal protective measures and also to change
their behaviour for employing improved water-storage practices like proper covering of
water-holding containers, use of larvicides, symptoms recognition for prompt treatmentseeking, etc.; (iii) for establishing a functional intersectoral mechanism of coordination
between all stakeholders for implementation of an integrated vector management approach;
(iv) for sensitization of local authorities for regular water supply and proper solid waste
management; and (v) for regular capacity building programmes. Operational research on
insecticide resistance in dengue vector(s), characteristics of virus, vector(s) densities and
bionomics between high- and low-affected areas, rural and urban areas, frequency of hostvector contact and disease epidemiology is also strongly recommended, which ultimately
would lead to the development of an evidence-based, community-friendly and sustainable
disease management strategy in the country.
Acknowledgement
We gratefully acknowledge the support received from the district health offices and district
governments of the selected districts. The efforts for data management made by Mr Muazzam
Abbas and Dr Mumtaz Ali Khan of the Epidemic Investigation Cell, National Institute of
Health, are highly appreciated. We especially would like to thank Mr Muhammad Shafiq,
Mr Imam Bukhsh Keerio, Mr Mukhtiar Ahmed Channa and Mr Mir Ali Talpur for their great
dedication to facilitate our mission. The authors would also like to express their appreciation
to the people of the Union Councils of these districts for their kind cooperation throughout
the study.
References
[1] World Health Organization. Dengue and dengue haemorrhagic fever. Fact sheet no.117 March 2009.
Geneva: WHO, 2009. - http://www.who.int/mediacentre/factsheets/fs117/en/ - accessed 12 January
2012.
112
[2] Foo LC, Lim TW, Lee HL, Fang R. Rainfall, abundance of Aedes aegypti and dengue infection in Selangor,
Malaysia. Southeast Asian J Trop Med Public Health. 1985; 16: 560-68.
[3] Hales S, de Wet N, Maindonald J, Woodward A. Potential effect of population and climate changes on
global distribution of dengue fever: an empirical model. Lancet. 2002; 360 (9336): 830-34.
[4] Hii YL, Rocklöv J, Ng N, Tang CS, Pang FY, Sauerborn R. Climate variability and increase in incidence
and magnitude of dengue incidence in Singapore. Global Health Action. 2009 Nov 11; 2. doi: 10.3402/
gha.v2i0.2036.
[5] Bartley LM, Donnelly CA, Garnett GP. The seasonal pattern of dengue in endemic areas: mathematical
models of mechanisms. Trans Roy Soc. Trop Med Hyg. 2002; 96(4): 387-97.
[6] Reisen WK, Milby MM. Population dynamics of some Pakistan mosquitoes: changes in adult relative
abundance over time and space. Ann Trop Med Parasitol. 1986; 80: 53-68.
[7] Yang HM, Macoris MLG, Galvani KC, Andrighetti MTM, Wanderley DMV. Assessing the effects of
temperature on the population of Aedes aegypti, the vector of dengue. Epidemiol Infect. 2009; 137:
1188-1202.
[8] Eisenhut M, Schwarz TF, Hegenscheid B. Seroprevalence of dengue, chikungunya and Sindbis virus
infections in German aid workers. Infection. 1999; 27(2): 82-85.
[9] Halstead SB. Global epidemiology of dengue hemorrhagic fever. Southeast Asian J Trop Med Public
Health. 1990; 21: 636–41.
[10] Humaira Z, Dhodhy M, Hayyat A, Akhtar N, Rizwan F, Chaudhary B, Zareef S. Seroprevalence of
dengue viral infection in healthy population residing in rural areas of district Rawalpindi. International
J Pathology. 2010; 8(1):13-16.
[11] Qureshi JA, Notta NJ, Salahuddin N, Zaman V, Khan JA. An epidemic of dengue fever in Karachi:
associated clinical manifestations. J Pak Med Assoc. 1997; 47: 178-81.
[12] Ali N, Nadeem A, Anwar M, Tariq W, Chotani RA. Dengue fever in malaria endemic areas. J Coll Phy
Surg Pak. 2006; 16: 340-2.
[13] Riaz MM, Mumtaz K, Khan MS, Patel J, Tariq M, Hilal H, Sadiqui AS, Shahzad F. Outbreak of dengue
fever in Karachi 2006: A clinical perspective. J Pak Med Assoc. 2009; 59(6): 339-44
[14] Gubler DJ. Aedes aegypti and Aedes aegypti borne disease control in the 1990s: top down or bottom
up. Am J Trop Med Hyg. 1989; 40 571-78.
[15] Kittayapong P, Strickman D. Distribution of container-inhabiting Aedes larvae (Diptera: Culicidae) at a
dengue focus in Thailand. J Med Entomol. 1993; 30: 601-06.
[16] Thavara U, Tawatsin A, Phan-Urai P, Ngamsuk W, Chansang C, Liu M, Li Z. Dengue vector mosquitoes at a
tourist attraction, Ko Samui, in 1995. Southeast Asian J Trop Med Public Health. 1996; 27(1):160-63.
[17] Sharma SK. Entomological investigations of DF/DHF outbreak in rural areas of Hissar District, Haryana,
India. Dengue Bulletin. 1998; 22: 167-70.
[18] Strickman D, Kittayapong P. Dengue and its vectors in Thailand: introduction to the study and seasonal
distribution of Aedes larvae. Am J Trop Med Hyg. 2002; 67(3): 247-59.
[19] Government of Pakistan. Federal Bureau of Statistics. Planning & Development Division II- Ministry of
Economic Affairs and Statistics. 2006. pp 102.
113
[20] Government of Pakistan. Population Census Organization. 2006. http://www.census.gov.pk/Statistics.
php - accessed 13 January 2012.
[21] Leopoldo MR. Pictorial key for the identification of mosquitoes (Diptera: Culicidea) associated with
dengue virus transmission. Zootaxa. 589. 2004; Pp 60.
[22] Mukhtar M, Jeroen E, Wim van der Hoek, Felix PA, Konradsen F. Importance of waste stabilization
ponds and wastewater irrigation in the generation of vector mosquitoes in Pakistan. J Med Entomol.
2006; 43(5): 996-1003.
[23] Reisen WK, Siddiqui TF, Aslamkhan M, Malik GM. Larval interspecific associations and physicochemical relationships of the ground-water breeding mosquitoes of Lahore. Pak J. Sc. Research. 1981;
3: 1-23.
[24] Thavara U, Tawatsin A, Chansang C, Kongngamsuk W, Paosriwong S, Boon-Long J, Rongsriyam Y,
Komalamisra N. Larval occurrence, oviposition behavior and biting activity of potential mosquito vectors
of dengue on Samui Island, Thailand. J Vector Ecol. 2001; 26(2): 172-80.
[25] Chen CD, Seleena B, Nazni WA, Lee HL, Masri SM, Chiang YF, Azirum MS. Dengue vector surveillance
in endemic areas in Kuala Lumpur City Center and Selangor State, Malaysia. Dengue Bulletin. 2006;
8: 197-03.
[26] Sulaiman S, Pawanchee ZA, Jeffert J, Ghauth I, Busparani V. Studies on the distribution and abundance
of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in an endemic area of dengue/dengue
haemorrhagic fever in Kuala Lumpur. Mosquito-Borne. Diseases Bulletin. 1991; 8 (2):35-39.
[27] Abdalmagid MA, Alhusein SH. Entomological investigation of Aedes aegypti in Kassala and Elgadarief
States, Sudan. Sudanese J. Public Health. 2008; 3 (2): 77-80.
[28] Isaacs N. Measuring Inter Epidemic Risk in Dengue Endemic Rural Area Using Aedes larval indices.
Indian J. Com Medicine. 2006; 31(3): 187-88.
[29] Seng CM, Jute N. Breeding of Aedes aegypti (L.) and Aedes albopictus (Skuse) in urban housing of Sibu
town, Sarawak. Southeast Asian J Trop Med Public Health. 1994; 25(3): 543-48.
[30] Cruz EI, Salazar FV, Porras E, Mercado R, Orais V, and Juancho, B. Entomological survey of dengue vectors
as basis for developing vector control measures in Barangay Poblacion, Muntinlupa City, Philippines,
2008. Dengue Bulletin. 2008; 32: 167-70.
[31] Higa Y, Yen TN, Kawada H, Son TH, Hoa TN, Takagi M. Geographic Distribution of Aedes aegypti and
Aedes albopictus Collected from Used Tires in Vietnam. J Am Mosq Cont Assoc. 2010; 26(1):1-9.
[32] Tsuda, Y, Suwonkerd W, Chawprom S, Prajakwong S, Takagi M. Different spatial distribution of Aedes
aegypti and Aedes albopictus along an urban-rural gradient and the relating environmental factors
examined in three villages in northern Thailand. J Am Mosq Control Assoc. 2006; 22: 222-28.
[33] Kittayapong P, Uruyakorn C, Chitti C, Amaret B. Community participation and appropriate technologies
for dengue vector control at transmission foci in Thailand. J Am Mosq Cont Assoc. 2006; 22(3): 53846.
[34] Ishak H, Miyagi I, Toma T, Kamimura K. Breeding habitats of Aedes aegypti (L) and Aedes albopictus
(Skuse) in villages of Barru, South Sulawesi, Indonesia. Southeast Asian J Trop Med Public Health. 1997;
28(4): 844-50.
114
[35] Schultz GW. Seasonal abundance of dengue vectors in Manila, Republic of the Philippines. Southeast
Asian J T Med Public Health. 1993; 24(2): 369-75.
[36] Suleman M, Khan K, Khan S. Ecology of mosquitoes in Peshawar valley and adjoining areas: species
composition and relative abundance. Pak J Zool. 1993; 25(4): 321-28.
[37] Kalra NL, Wattal BL, Raghvan NGS. Distribution pattern of Aedes (Stegomyia) aegypti in India – Some
ecological considerations. Bull Ind Soc Mal Com Dis. 1968; 5(3) 307-334.
[38] Khan MA, Sulman C. The bionomics of the mosquitoes of the Changa Manga National Forest, West
Pakistan. Pak. J. Zoology. 1969; 1(2):183-05.
[39] Li CF, Lim TW, Han LL, Fang R. Rainfall, abundance of Aedes aegypti and dengue infection in Selangor,
Malaysia. Southeast Asian J Trop Med Public Health. 1985; 16(4): 560-68.
115
Geographical association between socioeconomics
and age of dengue haemorrhagic fever patients in
Surabaya, Indonesia
Yoshiro Nagao,a# Esty M. Rachmie,b Shiro Ochi,c Maria M. Padmidewi,d
Kuntariantoe & Masato Kawabataa
International Centre for Medical Research and Treatment, Kobe University, Kusunoki,
Chuo-ku, Kobe, Hyogo, Japan.
a
Public Health Bureau of Surabaya City, Jalan Jemursari, No. 197, Surabaya, Indonesia.
b
Department of Environmental Management, Faculty of Agriculture, Kinki University, Nara, Japan
c
d
Public Health Laboratory of East Jawa, Jalan Karangmenjangan, No. 18, Surabaya, Indonesia
Public Health Bureau of East Jawa, Jalan A. Yani, No. 118, Surabaya, Indonesia
e
Abstract
A study was designed to correlate the ages of dengue patients to the geographical and temporal
demographic structure in 28 districts in Surabaya, Indonesia, between 1996 and 2005. The
geographical distribution of the mean patient age was stable throughout the study period. The mean
patient age did not correlate with the demographic structure but was related to the prevalence
of poor housing where mosquito density was high. These results suggested that socioeconomic
factors which affect mosquito abundance are more important determinants of the mean age of
DHF patients than the demographic variables.
Keywords: Demographic structure; Geographical distribution; Socioeconomics; Satellite imagery; Geographical
information system; Urbanization; Poverty; Islam; Surabaya; Indonesia.
Introduction
Although dengue illnesses affected predominantly small children until the 1970s, the mean
age of dengue illnesses has been shifting to adult populations in many south-east Asian
countries[1] such as Singapore,[2-4] Thailand[5,6] and Indonesia.[7,8] These observations led to
a hypothesis that the mean ages of dengue illnesses are a reverse indicator of mosquito
abundance and that increases in the mean ages of dengue patients reflect decreases in
#
116
Dengue in Surabaya, Indonesia
mosquito abundance.[9-11] However, an alternative hypothesis was proposed, which assumed
that mean age of patients with dengue illnesses indicates the demographic structure of the
population.[12] In a population with a larger proportion of young children, the mean age of
patients would be lower.
To date, however, no study has examined actual data to explore the determinant(s) of
the mean age of patients with dengue illnesses. The present study obtained the mean age of
patients of dengue haemorrhagic fever (DHF) from each district in Surabaya, the second largest
city in Indonesia. This variable was regressed against the socioeconomic and demographic
variables at the district level to identify factors that affected the mean patient age.
Study area
Surabaya is approximately 30 km × 20 km (375 km2) in size and is divided into 28 districts
(Figure 1). Numerous modern buildings are located in the centre of the city, while poorlyconstructed houses are situated on the banks of rivers, especially in the northern coastal
area. Although these houses have been threatened by occasional flooding, social intervention
programmes to relocate the residents have not made much progress.[13,14] For this study, a
digital map of Surabaya City was generated based on the official map, using PC-Mapping
Auto-Tracer (MAPCOM, Tokyo) and Mapinfo 7.0 (New York).
Figure 1: Location of Surabaya, Indonesia
(Surabaya is divided into 28 districts)
117
Epidemiological data
Individual DHF cases are reported daily to the Public Health Bureau of Surabaya City (PHBSC)
by public health stations (puskesmas), to which private and public hospitals are obliged to
report DHF cases. Each hospital was instructed by PHBSC to follow the WHO’s diagnostic
criteria for DHF.[15,16] Blood samples from ambiguous cases were sent to the Public Health
Laboratory of East Java for confirmation of diagnosis. The reports sent to PHBSC were recorded
on paper and subsequently compiled into an electronic format. Since age and residential
address were not included in the electronic records, only paper records were used in this
study. As a result, only the paper records from 1996, 1997, 1998, 2002, 2003 and 2005
were available from the archives. In total, 10 564 cases of DHF were reported during these
six years. Ages and residential addresses were available for 10 079 (95%) of the reported
cases, and only these cases were included in the analysis. The size of the population in each
district was obtained from the annual reports from the Statistics Bureau of Surabaya City. The
population of Surabaya city was 2 344 520 in 1996 and 2 629 001 in 2005.
Detection of spatial clustering of epidemiological variables
To interpret the geographical distribution of the epidemiological variables quantitatively, we
employed the Getis-Ord Gi statistic,[17] which detects ‘positive cluster’ (spatial clustering of
large values) and ‘negative cluster’ (clustering of small values). For this and subsequent spatial
analyses, a binary distance matrix was required. Each element of the binary distance matrix
was coded “1” if a pair of district centres was within a pre-defined neighbourhood cut-off
distance or “0” otherwise. Since the longest minimum distance between district centres was
5.8 km and the shortest maximum distance was 12 km, we defined the neighbourhood cutoff distance as 9 km, the average of those two distances.
Demographic/socioeconomic variables
The correlation between the mean patient age and demographic/socioeconomic data was
investigated at the district level. These socioeconomic/demographic datasets were obtained
from the above-mentioned annual reports from the Statistics Bureau of Surabaya City, and
are defined in Table 1. Among these variables, the birth rate and primary school attendance,
which represents 94% of children aged 7 to 12 years in Indonesia,[18] are reliable indicators
of the age structure. When a variable was missing for a specific district in any given year, its
value was interpolated by averaging the values from the years before and after the missing
year. Two exceptions were ‘poor housing’ and ‘family size’ in Table 1: the former was reported
only in 2005, and the latter was reported only in 2002. We used the values in these years
for the whole study period.
118
Table 1: Demographic/socioeconomic/geographic variables employed
as explanatory variables
Variable name
Definition
1. Birth rate
New births per 1000 individuals per year
2. Population density
Population per 1 km2
3. Mortality
Deaths per 1000 individuals per year
4. Immigrants
Incoming population per 1000 individuals per year
5. Emigrants
Outgoing population per 1000 individuals per year
6. Primary school pupils
Number of pupils in primary school (state, private, and
Islamic) per 1000 individuals
7. State junior high school
Number of state junior high school students per 1000
individuals
8. Private junior high school
Number of private junior high school students per 1000
individuals
9. State senior high school
Number of state senior high school students per 1000
individuals
10. Private senior high school
Number of private senior high school students per 1000
individuals
11. Kindergarten children
Number of kindergarten children per 1000 individuals
12. Islamic education
Percentage of Islamic primary school pupils in the total
number of primary school pupils
13. Garbage
Per capita volume of garbage (m3) collected daily
14. Park areas
Percentage of park area in total size of district
15. Agricultural areas
Percentage of agricultural area in total size of district
16. Poor housing
Percentage of poorly constructed housings
17. Public physicians
Number of physicians of public health station per 1000
individuals
18. Family size
Number of members per family
19. Coastal district
Coded as 1 for a district that faces the sea or 0 for a district
that does not face the sea
20. High-density residential
Percentage of high density residential area in the total district
area
students
students
students
students
areas
119
Geographical variable and satellite imagery
Geographical heterogeneity, such as the presence of the sea, may affect the district climate,
which is an important determinant of the transmission intensity. To adjust for this effect, a
dummy variable indicating whether a district faces the sea or not was incorporated into the
statistical analysis. The heterogeneity in land use (for example, the degree of aggregation
of premises) may also affect the probability of movement of vector mosquitoes from house
to house. To consider this possibility and incorporate a variable independent of official
publications, we estimated the percentage of ‘high density residential areas’ (Table 1) for
each district using satellite imagery data. Briefly, raw data recorded on 11 July 2009 by
the Advanced Visible and Near Infrared Radiometer type 2 loaded on the Advanced Land
Observation Satellite was segmented.[19] Normalized Difference Vegetation Index (NDVI)
was estimated for each segment.[20,21] Land use was classified into ‘factories’, ‘residential
areas’ and ‘crop land’ using the standard supervised classification method based on NDVI
(Figure 2). With a cut-off NDVI of −0.2, residential areas were divided into high- and lowdensity residential areas (Figure 3).
Figure 2: Map of residential density
(Using satellite image data, high-density residential areas (green) and low-density
residential areas (red) were identified)
120
Figure 3: Algorithm used to classify satellite imagery objects
(Using the algorithm described in this figure, residential areas were identified from the
satellite image data and classified into high- and low-density residential areas, based on
the Normalized Difference Vegetation Index (NDVI))
Image
Image object
NDVI < 0.6
NDVI > 0.6
Water
Land
NDVI < 0.2
NDVI > 0.2
Supervised classification
Factories
Residential area
NDVI < 0.2
High-density residential area
Crop land
Forest & Agricultural field
NDVI > 0.2
Normal density residential area
Stata 9.2 was used for the statistical analyses. As a screening process, we selected the
socioeconomic variables that exhibited a significant rank correlation (P<0.05) with the mean
age of patients. For this analysis, the overall dataset was prepared in which the mean patient
age was estimated from patient records pooled over the six years, while the socioeconomic/
demographic variables were averaged from those six years. The selected variables were
then incorporated into the subsequent regression analyses. We employed spatial regression
analysis and longitudinal regression analysis. In both analyses, independent variables that
did not make a statistically significant contribution to the regression model were eliminated
one at a time (Wald’s test).
121
Spatial regression analysis
The bias from spatial autocorrelation was adjusted for, using the spatial regression analysis
with lag model.[22] The neighbourhood cut-off distance was set to 9 km as mentioned above.
The above-mentioned overall dataset aggregated from the 6 years was used.
Longitudinal regression analysis
To consider the inter-annual variation, we employed the random effect linear regression
model. The data recorded for the individual years were used for this analysis. Year was
incorporated as an independent variable to represent the temporal trend.
Results
Epidemiology of DHF
Table 2 summarizes the epidemiological data used in the analysis. As shown in Table 2, the
annual incidence was highly unstable. The geographical distributions of this variable supported
this observation, showing apparently unpredictable patterns (Figure 4). On the other hand,
Figure 4: Geographical distribution of the incidence of DHF
(Districts are classified based on the annual incidence of DHF cases
(per 100 000 individuals))
122
†
2 356 386
2 431 348
2 431 501
2 553 022
2 629 001
2 457 630
1997
1998
2002
2003
2005
Overall
period†
10 564
2677
835
1569
2280
1328
1875
18.0
15.2
18.5
18.2
19.9
20.4
17.7
Mean age
of DHF
patients
(years)
71.6
102
32.7
64.5
96.8
56.4
80.0
Annual
incidence
of DHF
(per
100 000)
Cases from 6 years (1996, 1997, 198, 2002, 2003, and 2005) are aggregated.
2 344 520
1996
Population
Number
of DHF
patients
Surabaya as a whole
33 597−208 333
34 687−214 062
32 761−211 686
25 580−215 833
29 473−206 479
21 196−205 414
20 834−203 749
Population
96−960
32−236
3−81
5−169
10−235
5−125
9−212
Number
of DHF
patients
11.4−23.8
9.25−20.7
6.33−26.7
6.10−23.7
12.3−27.2
11.4−30.0
8.06−24.0
Mean age
of DHF
patients
(years)
Range, at the district level
Table 2: DHF statistics for Surabaya, Indonesia
45.8−124
42.5−194
7.33−89.5
27.4−177
14.8−182
12.1−120
22.8−211
Annual
incidence
of DHF
(per
100,000)
123
the geographical distribution of the mean age of patients was stable: consistently high in
the south-eastern districts and low in the north-western districts (Figure 5). Furthermore,
this was supported by the geographical clusters of the mean patient age: a positive cluster
persisted in the south-eastern region while a negative cluster existed in the north-western
region throughout the study period (Figure 6).
Explanatory variables
Table 3 summarizes the individual explanatory variables and their rank correlations with
mean age of DHF patients. The following variables exhibited significant rank correlation with
mean age of patients: emigrants (P=0.0320), private junior high school students (P=0.0472),
private senior high school students (P=0.0118), kindergarten children (P=0.0007), Islamic
education (P=0.0001), garbage (P=0.0354), agricultural area (P=0.0395), and poor housing
(P=0.0021).
Figure 5: Geographical distribution of the mean age of DHF patients
(Districts are classified based on the mean age of DHF patients (in years) in individual
study years or over all 6 years combined)
124
Figure 6: Geogaphical clusters of the mean age of DHF patients
(Districts are classified based on statistical significance of the Getis-Ord Gi statistic,
estimated from the mean age of DHF patients. Positive cluster represents clustering of
large values, while negative cluster represents clustering of small values)
Spatial and longitudinal regression analyses
From these eight variables, only those exhibiting significant contribution to the statistical
model were selected by Wald’s test. Private senior high school students, Islamic education
and poor housing were selected by spatial regression analysis (column (a) of Table 4). The
longitudinal regression analysis selected private senior high school students, poor housing
and year (column (b) of Table 4).
Geographical distribution of selected variables
Table 4 indicates that in both spatial and random-effect regression analyses, two factors
showed statistically significant contribution to the mean age of patients: private senior high
school students as a positive contributor and poor housing as a negative contributor. Therefore,
we selected these two variables as the most robust predictors of the mean age of patients. The
relationship between these variables and mean age of patients is shown in Figure 7. Figure 8
shows the geographical distribution of these socioeconomic/demographic variables.
125
Table 3: Summary of district attribute variables averaged through the study period and
rank correlations with mean age of DHF patients
Mean
Range
Rank correlation
with mean patient
age and (P)
12
9.5 − 19
−0.096 (P=0.6278)
12 057
819 − 40,333
−0.091 (P=0.6437)
3. Mortality (per 1000)
3.6
2.6 − 5.1
−0.15 (P=0.4496)
4. Immigrants (per 1000)
20
8.6 − 53
0.22 (P=0.2618)
5. Emigrants (per 1000)
16
9.4 − 22
0.41 (P=0.0320)
6. Primary school pupils (per 1000)
111
57 − 149
0.23 (P=0.2302)
19
0 − 67
−0.0082
(P=0.9668)
29
7.6 − 61
0.38 (P=0.0472)
11
0 − 98
−0.021 (P=0.9165)
21
0 − 85
0.47 (P=0.0118)
11. Kindergarten children (per 1000)
28
12 − 49
0.60 (P=0.0007)
12. Islamic education (%)
10
0.26 − 34
−0.66 (P=0.0001)
0.0030
0.00137 −
0.00562
0.40 (P=0.0354)
0.30
0 − 1.8
0.31 (P=0.1116)
15. Agricultural areas (%)
41
0 – 94
0.39 (P=0.0395)
16. Poor housing (%)
17
5.1 – 41
−0.56 (P=0.0021)
17. Public physicians (per 1000)
0.042
0.019 − 0.074
0.24 (P=0.2106)
18. Family size (per family)
3.68
3.15 – 3.93
−0.37 (P=0.0520)
19. Coastal district (binary)
0.36
0–1
−0.19 (P=0.3231)
31
0.75 − 85
−0.039 (P=0.8422)
Variable name
1. Birthrate (per 1000)
2. Population density (per square
kilometer)
7. State junior high school students
(per 1000)
8. Private junior high school students
(per 1000)
9. State senior high school students
(per 1000)
10. Private senior high school students
(per 1000)
13. Garbage (cubic meters per person)
14. Park areas (%)
20. High density residential areas (%)
Bold text indicates statistical significance.
126
Table 4: Regression models to explain mean age of DHF patients
(a)
Spatial regression with
selected variables
(n=28)
(b)
Random-effect regression
with selected variables
(n=168)
Coefficient (P)
Coefficient (P)
Private senior high school
students
0.048 (P=0.005)
0.069 (P=0.006)
Islamic education
−0.13 (P=0.002)
Poor housing
−0.099 (P=0.008)
−0.17 (P=0.001)
not used
−0.25 (P<0.001)
R2=0.74
R2=0.28
Year
Figure 7: Mean age of DHF patients plotted over socioeconomic variables
(Mean age of DHF patients estimated over all 6 years was plotted over socioeconomic
variables. Please note the remarkable dependence of mean age of patients upon poor
housing (A), private senior high school (B), and Islamic education (C). Three demographic
variables [birth rate (D), primary school attendance (E), and mortality (F)] did not show
relationship to the mean age of patients)
127
Figure 8: Geographical distribution of socioeconomic variables
(Districts were classified based on the socioeconomic or demographic variables.
The geographical distributions of poor housing (A) and Islamic education
(B) overlapped with that of low mean age of patients (Figure 5 and Figure 6).
On the contrary, the geographical distribution of private senior high school attendance
(C) overlapped with that of high mean age of patients. None of the demographic variables
[birthrate (D), primary school attendance (E) and mortality (F)] showed geographical
distribution related to mean patient age)
Discussion
The geographical distribution of the mean age of patients in Surabaya was stable during the
study period (Figure 5 and Figure 6). We subsequently found that the mean patient age was
related negatively to the prevalence of poor housing, but positively to the use of private
senior high schools. These results may be interpreted as follows: in developing countries, poor
premises are not equipped with window screens or air-conditioners, which hinder entry of
mosquitoes.[23,24] In addition, poor premises are not supplied with piped water and they rely
on household water containers. Therefore, poor housing provides ideal breeding places for
Aedes.[25-27] In contrast, private senior high school attendance may indicate economic wealth,
which affords window screens, air-conditioners and piped water supply. Alternatively, private
senior high school attendance may reflect the educational level and awareness important
for mosquito reduction.
Therefore, the findings from this study are consistent with the hypothesis that the mean
age of DHF patients is a reverse indicator of Aedes abundance. On the other hand, in
128
Surabaya, the geographical distribution of the mean age of DHF patients was not associated
with any demographic variables examined (Table 3, Table 4, Figure 7). This implies that the
socioeconomic factors that surrogated Aedes abundance were more influential determinants
of the mean age of DHF patients than demographic variables.
The present study will not negate the importance of socioeconomic factors other than
those which remained in the final statistical models (i.e. private senior high schools and poor
housing). For example, family size, which showed a non-significant but considerable rank
correlation with mean patient age (Table 3), may indicate vulnerability to dengue transmission
among family members. The small sample size and dependence on the official publications
may have blunted the statistical power of the present study. Further study with a wider
spatio-temporal spread as well as diverse sources of information is warranted.
Acknowledgements
We are grateful to Atsushi Yamanaka for collecting official publications from Surabaya, and
to Tony Pilkington for assistance with geographical data preparation.
References
[1] Guha-Sapir D, Schimmer B. Dengue fever: new paradigms for a changing epidemiology. Emerg Themes
Epidemiol. 2005; 2:1.
[2] Ooi EE, Hart TJ, Tan HC, Chan SH. Dengue seroepidemiology in Singapore. Lancet. 2001; 357: 685686.
[3] Ooi EE, Goh KT, Chee Wang DN. Effect of increasing age on the trend of dengue and dengue hemorrhagic
fever in Singapore. International Journal of Infectious Diseases. 2003; 7: 231-232.
[4] Ooi EE, Goh KT, Gubler DJ. Dengue prevention and 35 years of vector control in Singapore. Emerging
Infectious Diseases. 2006;12: 887-893.
[5] Chareonsook O, Foy HM, Teeraratkul A, Silarug N. Changing epidemiology of dengue hemorrhagic
fever in Thailand. Epidemiology and Infection. 1999;122: 161-166.
[6] Nagao Y, Svasti P, Tawatsin A, Thavara U. Geographical structure of dengue transmission and its
determinants in Thailand. Epidemiology and Infection. 2008; 136: 843-851.
[7] Sumarmo. Dengue haemorrhagic fever in Indonesia. Southeast Asian Journal of Tropical Medicine and
Public Health. 1987; 18: 269-274.
[8] Setiati T, Wagenaar, JFP., Kruif, MD., Mairuhu ATA., Gorp ECM., Soemantri A. Changing epidemiology
of dengue haemorrhagic fever in Indonesia. Dengue Bulletin. 2006; 30: 1-14.
[9] Egger JR, Ooi EE, Kelly DW, Woolhouse ME, Davies CR, Coleman PG. Reconstructing historical changes
in the force of infection of dengue fever in Singapore: implications for surveillance and control. Bulletin
of the World Health Organization. 2008; 86: 187-196.
129
[10] Nagao Y, Koelle K. Decreases in dengue transmission may act to increase the incidence of dengue
hemorrhagic fever. Proceedings of the National Academy of Sciences of the United States of America.
2008;105: 2238-2243.
[11] Thammapalo S, Nagao Y, Sakamoto W, Saengtharatip S, Tsujitani M, Nakamura Y, Coleman PG,
Davies C. Relationship between Transmission Intensity and Incidence of Dengue Hemorrhagic Fever
in Thailand. PLoS Negl Trop Dis. 2008; 2: e263.
[12] Cummings DA, Iamsirithaworn S, Lessler JT, McDermott A, Prasanthong R, Nisalak A, Jarman RG, Burke
DS, Gibbons RV. The impact of the demographic transition on dengue in Thailand: insights from a
statistical analysis and mathematical modeling. PLoS Med. 2009; 6: e1000139.
[13] Santosa H. Community participation in the upgrading of informal settlement and housing at the river
bank of Surabaya. CIB World Building Congress. 2007. 2007:1964-1971.
[14] Wibowo A. Segmental development design for Wonokromo waterfront settlements at Surabaya. Informal
Settlements and Affordable Housing; 2007. Semarang, 2007.
[15] WHO. Dengue haemorrhagic fever: diagnosis, treatment and control. Geneva: 1986.
2nd edition. Geneva: WHO, 1997.
[17] Getis A, Ord JK. The analysis of spatial association by use of distance statistics. Geographical Analysis.
1992; 24: 189-206.
[18] UNICEF. Basic education for all. Indonesia. 2009. http://www.unicef.org/indonesia/education.html
[19] Earth Observation Research Center JAEA. Advanced land observation satellite, advanced visible and
near infrared radiometer type 2 (AVNIR-2). http://www.eorc.jaxa.jp/ALOS/en/about/avnir2.htm - 12
January 2012.
[20] Wang L, Sousa W, Gong P. Integration of object-oriented and pixel-based classification for mapping
mangroves with IKONOS imagery. International Journal of Remote Sensing. 2004; 25: 5655-5668.
[21] Tucker C. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing
of Environment. 1979; 8: 127-150.
[22] Anselin L, Hudak S. Spatial econometrics in practice. A review of software options. Regional Science
and Urban Economics. 1992; 22: 509-536.
[23] Waterman SH, Novak RJ, Sather GE, Bailey RE, Rios I, Gubler DJ. Dengue transmission in two Puerto
Rican communities in 1982. American Journal of Tropical Medicine and Hygiene. 1985; 34: 625632.
[24] Thammapalo S, Chongsuwiwatwong V, Geater A, Lim A, Choomalee K. Socio-demographic and
environmental factors associated with Aedes breeding places in Phuket, Thailand. Southeast Asian
Journal of Tropical Medicine and Public Health. 2005; 36: 426-433.
[25] Tun-Lin W, Kay BH, Barnes A. The Premise Condition Index: a tool for streamlining surveys of Aedes
aegypti. American Journal of Tropical Medicine and Hygiene. 1995; 53: 591-594.
[26] Barrera R, Navarro JC, Mora JD, Dominguez D, Gonzalez J. Public service deficiencies and Aedes aegypti
breeding sites in Venezuela. Bulletin of the Pan American Health Organization. 1995; 29: 193-205.
[27] Sharma K, Angel B, Singh H, Purohit A, Joshi V. Entomological studies for surveillance and prevention
of dengue in arid and semi-arid districts of Rajasthan, India. J Vector Borne Dis. 2008; 45:124-132.
130
Aedes aegypti indices and KAP study in Sangam Vihar,
south Delhi, during the XIX Commonwealth Games,
New Delhi, 2010
R.K. Singh,a P.K. Mittal,a N.K. Yadav,b O.P. Gehlotb & R.C. Dhimana#
National Institute of Malaria Research, Indian Council of Medical Research (ICMR),
Sector-8 Dwarka, New Delhi 110077, India.
a
Municipal Corporation of Delhi (MCD), Town Hall, Chandni Chowk, New Delhi 110006, India.
b
Abstract
Dengue fever (DF) cases were reported in Delhi during August 2010. As the XIXth Commonwealth
Games were to be held in Delhi in October 2010, entomological and community knowledge,
attitude and practices (KAP) studies were carried out to assist the Municipal Corporation of Delhi
(MCD) for better implementation of vector control activities in the city. A total of 495 houses were
searched for Aedes aegypti breeding in all kinds of temporary and permanent water receptacles
in both indoors and outdoors in a thickly-populated, illegally-constructed locality, named Sangam
Vihar, in south Delhi. The overall House Index (HI), Container Index (CI) and Breteau Index (BI)
were 44.44%, 19.01% and 91.92 respectively. For KAP, a pre-tested, structured questionnaire was
used for data collection. Out of the 384 households surveyed, 156 were aware about dengue
and only 12 households knew that virus was the causative agent for DF. A majority (378) of the
households practised water storage and 48 of them stored water for more than one week. No
preventive/control measures were adopted to prevent mosquito breeding in the water-holding
containers by a majority of the households (45.57%). 57% of them did not know the biting habits
of dengue vector mosquitoes.
The results of the study indicated that the community’s knowledge about dengue fever, its
transmission, vector breeding sources, biting habits and preventive measures was poor.
Keywords: Dengue; Aedes aegypti indices; Knowledge Attitude and Practices (KAP); Delhi.
Introduction
Delhi is endemic for dengue fever (DF)/dengue haemorrhagic fever (DHF) and has
experienced several outbreaks of DF/DHF since 1967.[1] In the recent past, an outbreak of
DF/DHF was recorded in 1996 which was most severe and resulted in more than 10 252
#
131
Aedes aegypti indices and KAP study in Sangam Vihar, New Delhi
hospitalizations and 423 deaths. All four dengue serotypes (DENV 1–4) are circulating in
the country.[2-3]
India hosted the XIX Commonwealth Games in Delhi from 3–14 October 2010. The
government expected a heavy influx of athletes and visitors during this period. In a bid
to prevent any upsurge of dengue, the Municipal Corporation of Delhi (MCD), which is
the agency mainly responsible for the control of vector-borne diseases, made elaborate
arrangements for the control of DF/DHF through public-private partnership (PPP), behavioural
change communication (BCC) and capacity-building activities.
To assist the MCD, the Ministry of Health and Family Welfare, Government of India
mobilized the services of scientists from two research institutes, viz. the National Institute
of Malaria Research (NIMR) under the Indian Council of Medical Research (ICMR) and the
National Centre for Diseases Control (NCDC), Ministry of Health and Family Welfare, all
located in Delhi, to undertake cross-check work for better implementation of vector control
activities. It was in that context, NIMR conducted the cross-check work in Sangam Vihar,
an area in south Delhi, known for the endemicity of DF/DHF. The activities covered an
assessment of Aedes aegypti indices and knowledge, attitude and practices (KAP) study in the
area which is a prerequisite for social mobilization and dengue prevention and control.[4] The
cross-check of indices were communicated to MCD for remedial action on a daily basis.
Study area
Delhi, with an area of 1485 sq km is located at 28.38° North latitude and 77.12° East
longitude. The climate of Delhi city is most varied. The lowest temperature ever recorded
was 2°C and highest 45°C, while relative humidity (RH) ranges from 20% to 86%. Delhi on
an average receives a rainfall of 212 mm during the rainy season (July to October). Sangam
Vihar is a part of the Central zone of MCD and the population of this area is about 400 000.
This locality has been built unauthorizedly, and those living in such settlements do not
receive piped water supply from Delhi Jal Board (DJB), the official agency responsible for
the supply of water to the city. The residents of Sangam Vihar, therefore, have to procure
water from private sources. They usually store water in overhead tanks (OHT) and groundlevel collection tanks (GLCT).
Entomological indices
A door-to-door survey was carried out in houses and in peri domestic areas to detect
Ae. aegypti breeding. The Aedes species was identified following Das and Kaul’s key.[5]
Entomological indices were collected as per sample size and techniques contained in the
WHO-SEARO guidelines.[6]
132
Knowledge, attitude and practices (KAP)
In selected households, door-to-door visits were made to fill up interview schedules (IS)
which emphasized four items: (i) knowledge on the causative agent of DF and mode of its
transmission; (ii) vector mosquito behaviour; (iii) community behaviour on water storage;
and (iv) mosquito control methods. A pre-tested, structured questionnaire was used for data
collection. The multistage cluster systematic method was applied. In the selected households,
mostly the head of the family or a member were interviewed after getting prior consent.
Of the 495 selected households, the IS could be filled up from 384 households only, the
others found locked at the time of visit. The study was carried out from 15 September to
15 October 2010.
Results
Aedes aegypti indices
A total of 495 houses in 21 localities were searched for Ae. aegypti breeding in all kinds of
water-holding receptacles kept both indoors and outdoors (open space inside the house
premises), of which 220 were found positive (Table 1). The House Index (HI), Container
Index (CI) and Breteau Index (BI) were 44.44%, 19.01% and 91.92 respectively. HI ranged
from 14.29% to 90%, CI ranged from 2.68% to 59.26% and BI ranged from 20 to 230.
The breeding preference ratio (BPR) was observed the highest (2.38) in discarded materials
lying outdoors, followed by evaporation room coolers (1.22), mud-pots (1.02) and domestic
small-to-large containers (0.87) placed indoors, respectively (Table 2). Maximum breeding
(35.82%) was detected in domestic storage (small-to-large) containers, followed by discarded
materials containing water (23.74%) and evaporation room coolers (16.04%). Discarded
tyres were found to be the least breeding habitats (3.73%). The results revealed that, out of
the 2394 water containers searched, 455 were found positive. Of the 401 overhead tanks
(OHTs) checked, 53 were found positive for Ae. aegypti breeding. Consumer items like
broken mud-pots and glassware and iron scraps were the most common items supporting
the breeding of Ae. aegypti. In addition, breeding was also observed in flower vases, old and
discarded plastic shoes, discarded/broken plastic items and other sites such as pick-holes of
manhole covers, plastic sheds, plastic bags and tea cups.
KAP
Table 3 shows the water storage practices in the households studied. The majority (61.98%)
of the households used small plastic and iron containers for water storage and 38.02% of
them used large containers. Only 12.5% of the households said that they stored water for
more than five days, while 1.6% of them said that they were getting sufficient water through
borewell and hence they did not require water to be stored for longer periods.
133
Table 1: Aedes aegypti indices in Sangam Vihar, New Delhi
Localities searched
block-wise
Houses
visited
Houses Containers Containers
positive searched positive
I-Block, slum colony
20
18
224
G-II/Street no. 18
21
8
F-I/Street no. 7
21
K-I/Street no. 18
HI
CI
BI
46
90.0
20.54
230.00
105
16
38.10
15.24
76.19
3
78
5
14.29
6.41
23.81
22
9
83
15
40.91
18.07
68.18
K-I/Bakari colony
21
3
86
15
14.29
17.44
71.43
J-II/Street no. 7
20
4
79
6
20.00
7.59
30.00
I/Street no. 10/21
21
10
97
21
47.62
21.65
100.00
I/Street no. 18
21
15
226
56
71.43
24.78
266.67
D-II/Street no. 2
20
3
77
4
15.00
5.19
20.00
J-I&II/Gupta colony
21
9
71
15
42.86
21.13
71.43
F-I Block
20
4
91
7
20.00
7.69
35.00
G-II/Street no. 19
20
14
95
24
70.00
25.26
120.00
F-II/E-7&D-5
10
2
27
3
20.00
11.11
30.00
I-Block/Street no. 4
20
13
91
24
65.00
26.37
120.00
J-I/Street no. 6&7
20
4
149
4
20.00
2.68
20.00
K-I/18D&19
20
7
113
13
35.00
11.50
65.00
K&I Block
21
12
110
31
57.14
28.18
147.62
E-6& D-5
25
12
191
36
48.00
18.85
144.00
I-II-Block
18
11
203
20
61.11
9.85
111.11
D-5, E-6&7
59
27
144
62
45.76
43.06
105.08
KI-18, K-19
54
32
54
32
59.26
59.26
59.26
Total
495
220
2394
455
44.44
19.01
91.92
134
Table 2: Breeding Preference Ratio (BPR) of Ae. aegypti in different breeding habitats
in Sangam Vihar, New Delhi
Number of containers with water
Indoor
(Domestic)
Outdoor
(Peridomestic)
Type of breeding habitats
Breeding
Preference Ratio
Examined
(X%)
With
larvae
(Y%)
BPR (Y/X)
Discarded materials
(viz. old plastic/glass
bottle/iron scrap)
239
9.98
108
23.74
2.38
Mud-pots
98
4.09
19
4.17
1.02
Discarded tyres
103
4.30
17
3.73
0.87
Domestic containers
(Small and Large)
1080
45.11
163
35.82
0.79
Evaporation coolers
315
13.16
73
16.04
1.22
*OHWTs
401
16.75
53
11.65
0.70
**GLCTs
158
6.67
22
4.83
0.73
Total
2394
455
*OHWT= Overhead water tank; **GLCT= Ground-level cement tank.
Table 3: Community behaviour about water storage practices for dengue control
No. surveyed
(384)
% used for
water storage
Small containers
(less than 25 litres)
Large containers
(more than 25 litres)
238
61.98
146
38.02
1-2 days
188
48.96
3-5 days
142
36.98
> 5 days
48
12.5
Do not store
6
1.6
Parameter
Type of container
Type of domestic containers
used by the community for
storage
Duration of water storage
in domestic water-holding
containers
135
A total of 384 households were interviewed and their demographic details are shown
in Table 4. 77.07% of the respondents had education up to the undergraduate level, 8.85%
were graduates and 14.06% were illiterate. Of the total households surveyed, 53.38% of
the respondents belonged to the below poverty line (BPL) category, while 43.22% belonged
to the middle-income level and 3.38% were from the high income group. 46.87% of the
respondents were unemployed.
The perception of the community about dengue and its related information is compiled in
Table 5. Only 40.62% of the respondents were aware that dengue is transmitted by a mosquito
bite, while a majority (56.25%) of them did not know the cause of the disease. Only 3.12%
knew that virus is the causative agent for DF. It was observed that the knowledge about DF
and its preventive methods was high among the formally-educated group (graduate level) as
compared to those educated up to undergraduate level. Of the 384 households, only 13.8%
knew that clean water-holding containers contributed to vector breeding. The remaining
respondents knew about various other sources of breeding of vector mosquitoes (Table 5).
45.57% of them said that they did not follow any preventive measures to control mosquito
breeding. 46.87% of them said that they followed some measures (viz. frequently cleaning
the containers and covering them); 5.46% removed the unused materials and unwanted
containers (Table 5). The respondents were asked whether dengue could be prevented.
About 14% replied that dengue was a preventable disease. The majority of the respondents
felt that keeping the surroundings clean and following general hygienic conditions would
Table 4: Demographic characteristics of the community surveyed
No. of HHs surveyed
% HH surveyed
Male
81
21.09
Female
303
78.90
Illiterate
54
14.06
Undergraduate
296
77.07
Graduate
34
8.85
Below poverty line
205
53.38
Middle-income group
166
43.22
High-income group
13
3.38
Service professional
156
40.62
Business/self-employed
42
10.93
Student
6
1.56
180
46.87
Variable
Sex
Educational status
Economic status
Employment
Respondent
Unemployed
136
Table 5: Community knowledge, attitude and practices (KAP) on dengue vector and its
control, Sangam Vihar, New Delhi
Responses (n=384)
S. No.
1
Details
No. of
HHs
%
Awareness of dengue fever
156
40.62
(ii) Virus is the cause of dengue fever
12
3.12
(iii) Not known
216
56.25
(iv) Can be prevented
55
14.32
(v) Cannot be prevented
21
5.46
(vi) Not known
308
80.20
(vii) Control mosquito by insecticides
16
4.16
(viii) By taking medical care
9
2.34
(ix) Keeping environment clean
47
12.23
(x) Taking medical care and keeping environment clean
5
1.30
(xi) No response
307
79.94
Knowledge on dengue vector breeding and biting
behaviour
145
37.76
72
18.75
53
13.80
114
29.86
(xvi) Removed unused materials
21
5.46
(xvii) Did not take control measures in domestic containers
175
45.57
(xviii) Followed control measures in discarded containers
180
46.87
(xix) Taken measures to avoid mosquito bite during daytime
(used net or repellents, etc.)
48
12.5
(xx) Used fan alone
299
77.86
37
9.63
Community knowledge on dengue
(i)
2
3
4
Perception of dengue prevention by community
Methods of dengue prevention adopted by community
(xii) Aware of day-biting behaviour of mosquitoes
(xiii) Dengue transmitted by mosquito bite
(xiv) Dengue mosquitoes breed in clean water
(xv) Not known
5
6
Practices of control of mosquito breeding
Practices of prevention of mosquito bite during day
(xxi) Did not take any measures during daytime
137
help prevent occurrence of the disease. 56.25% had poor knowledge about dengue, while
12.23% said that keeping the environment clean could help to prevent dengue fever and
14.32% had only moderate knowledge about dengue.
A total of 37.76% knew that dengue-transmitting mosquitoes bite during daytime while
62% did not know the biting behaviour of Ae. aegypti (Table 5). Irrespective of the knowledge
on dengue vector’s biting behaviour, nearly 10% of the households did not adopt any measure
to prevent mosquito bites, while 77.86% of them used only fans. About 12.5% took some
personal protection measures such as net or repellents, etc.
Discussion
During the survey, varying levels of density of larvae and adult mosquitoes of Ae. aegypti
were recorded at different sites in the study area. It was observed that unused or discarded
containers which were kept in open spaces within the house premises/indoors were rarely
cleaned and remained undisturbed most of the time, thus resulting in high breeding of
Ae. aegypti mosquitoes. Large water-storage containers were found to be the key breeding
sites.[7] Ae. aegypti breeding was also found in evaporation room coolers. These evaporation
coolers are well known for the breeding of Ae. aegypti mosquitoes during the monsoons in
Delhi.[8] But during the present study the positivity of evaporation coolers was low because
of the community’s practice of continuously refilling/re-introducing fresh water every day.
Our results showed that the majority of the population in Sangam Vihar, New Delhi,
has some amount of awareness about dengue fever because of several earlier DF outbreaks
in Delhi. In spite of this, Ae. aegypti breeding was very common in the study area. This was
due to the lack of preventive practices against Ae. aegypti mosquito breeding in household
containers. In the present study, only 45.57% of community members adopted some kind
of vector control measures in domestic water storage containers and 5.46% removed the
unused containers/materials. Lack of basic knowledge in the community about dengue and its
vector could also be a major cause of the increasing trend of dengue in this thickly populated
periurban environment.[9] In more than half of the area, water was being supplied through
water tankers, and in other areas by regular water supply.[10-11] Large ground-level cemented
tanks have been installed in house premises/indoors which are filled with water periodically.
These water-storage tanks become ideal breeding sites for Ae. aegypti mosquitoes, particularly
if water is stored for long durations without proper covers.[12]
IEC activities
The Municipal Corporation of Delhi (MCD) is undertaking various activities for health
education through the print and electronic media, vocal messages, street plays and pamphlets,
and by involving schoolchildren, for creating awareness about dengue fever. It was, therefore,
138
thought prudent to assess the community’s perception also about the impact of information
education and communication (IEC) activities on their KAP pertaining to water storage and
dengue control.
During the survey it was found that fogging operations generally lacked a pre-fogging
public information campaign which requires the houses to be kept open for the entry of
the fog. Health workers, while interacting with householders, invariably talked about the
removal of breeding from room coolers and overhead tanks but did not provide enough
information regarding pre-fogging requirements.
This study shows the occurrence of Ae. aegypti larvae and adults in Sangam Vihar area
in south Delhi during the transmission season. The preventive strategy here needs to be
directed at seeking active community participation in containing dengue cases in the future.[13]
The study revealed that although there was some awareness in the community about the
breeding of dengue vector inside their premises, there was a lack of perception to eliminate
these habitats due to one reason or the other.
Thus, there is a need to provide dependable regular water supply to the communities
and education for seeking their participation in destroying the breeding habitats of Ae. aegypti
mosquitoes, while enforcing stringent legal measures for mosquito control.
Acknowledgements
We are grateful to Mr N.L. Kalra for his useful suggestions. We also thank the technical staff
of NIMR and NCDC for their active involvement and assistance during the field survey.
References
[1] Balaya S, Paul SD, D’lima LV, Pavri KM. Investigations of an outbreak of dengue in Delhi in 1967. Ind
Jour Med Res. 1969; 57: 767-774.
[2] Kaul SM, Sharma RS, Sharma SN, Panigrahi N, Phukan PK, Shiv Lal. Preventing dengue and DHF - the
role of entomological surveillance. Jour Commun Dis. 1998; 30: 187-92.
[3] Nandi J, Sharma RS, PK Datta, Dhillon GPS. Dengue in the National Capital Territory (NCT) of Delhi
(India): epidemiological and entomological profile for the period 2003-2008. Dengue Bulletin. 2008;
(32): 156-161.
[4] Parks W, Lloyd L. Planning social mobilization and communication for dengue fever prevention and
control: a step-by-step guide. Geneva: World Health Organization, 2004.
[5] Das BP, Kaul SM. Pictorial key to the common Indian species of Aedes (stegomyia) mosquitoes. J Com
Dis. 1998; (30): 123-127.
[6] World Health Organization, Regional Office for South-East Asia. Prevention and control of fever and
dengue haemorrhagic fever: comprehensive guide lines. WHO Regional Publication SEARO No. 29.
New Delhi: WHO-SEARO, 1999.
139
[7] Padmanabha H, Soto E, Mosquera M, Lord CC, Lounibos LP. Ecological links between water storage
behaviors and Aedes aegypti production: implications for dengue vector control in variable climates.
Eco Health. 2010; 7(1): 78-90.
[8] Rakesh K, Gill KS, Kumar K. Seasonal variations in Aedes aegypti population in Delhi. Dengue Bull.
1996; 20:78-81.
[9] Bowondor B, Chetri R. Urban water supply in India: environmental issues. Urban Ecology. 1984; 8:
295-311.
[10] Government of NCT of Delhi. Economic survey of Delhi 2005-06. (http://delhiplanning.nic.in/
Economic%20Survey/ES%202005-06/Chpt/14.pdf - accessed 12 Jan 2012).
[11] Zerah MH. Water: Unreliable supply in Delhi. New Delhi: Centre De Sciences Humaines, 2000.
[12] Knudsen AB, R Slooff. Vector borne disease problem in rapid urbanization: New approaches to vector
control. Bulletin WHO. 1992; 70(1): 1-6.
[13] Kalra NL, GK Sharma. Malaria control in India – Past, present and future. Jour Commun Dis. 1987;
19(2): 91-116.
140
Pupal/demographic and adult aspiration surveys of
residential and public sites in Yogyakarta, Indonesia,
to inform development of a targeted source control
strategy for dengue
Sugeng J. Mardihusodo,a Tri Baskoro T. Satoto,a A. Garciab & Dana A. Focksc#
a
Department of Parasitology, Center for Tropical Medicine, Faculty of Medicine, Gedung Radioputro
Lt. 4, University of Gadjah Mada, Yogyakarta 55281, Indonesia.
Department of Geography and the Emerging Pathogens Institute, PO Box 100009, Biomathematics
Suite, 2055 Mowry Road, University of Florida, Gainesville, FL 32611, USA.
b
c
Department of Environmental and Global Health and the Emerging Pathogens Institute, PO Box
100009, Room 473, 2055 Mowry Road, University of Florida, Gainesville, FL 32611, USA.
Abstract
Pupal/demographic surveys can provide important information to help target vector control
activities. A small-scale pilot study conducted during 2005-06 was based upon earlier pupal/
demographic surveys (1996-1999) in one subdistrict of Yogyakarta in which a bathroom container
(bak mandi), a common water-storage container (typically buckets, ember/bak air), wells (sumur)
and used tyres (ban bekas) were identified as the most productive container types for Aedes
aegypti pupae. The present work extends these original pupal/demographic surveys to include
other subdistricts within the City of Yogyakarta to determine what types of containers need to be
targeted in a larger city-wide effort.
Pupal/demographic surveys and adult aspirations were conducted in January 2008 during the rainy
season in and around approximately 160 residences and public or commercial sites in each of six
subdistricts. In residential sites, the bak mandi accounted for 75% of all Ae. aegypti pupae; this
container and bak air/ember and tempayan tanah (clay water container) accounted for a total of
96% of all pupae observed. In public sites, the same container types were identified as being the
most productive, and again, the bak mandi was the most productive (62%). We concluded that the
types of containers to be targeted in the city-wide control effort would be the bak mandi and bak
air/ember, which would address 91% and 86% of all Ae. aegypti production in the above-ground
containers in residential and commercial sites respectively. As in the case of this pilot study, wells
could be a third type of container to be included because wells are known to be often Ae. aegyptipositive, although their exact contribution to pupal production is difficult to quantify.
Keywords: Dengue; Aedes aegypti; Pupal/demographic survey; Adult aspirations; Aedes albopictus; Targeted
source control strategy.
#
141
Pupal/demographic and adult aspiration survey Aedes aegypti in Yogyakarta, Indonesia
Introduction
Dengue has been endemic in the City of Yogyakarta and its adjacent districts (kabupaten)
since 1972 and is currently found in all its 45 subdistricts (kelurahan). The primary vector
is Aedes aegypti.[1] The initial pupal/demographic surveys in Gondokusuman indicated that
Ae. aegypti pupae were found in both indoor and outdoor containers and that the number
of pupae in outdoor containers increased during the rainy season. For this reason, the surveys
described here were conducted during the rainy season.[2] Other mosquitoes present in the
urban environment included Aedes albopictus and Culex spp.[2]
Yogyakarta, a city of approximately 522 000 people, is the provincial capital of the
province or Special Region of Yogyakarta (Daerah Istimewa Yogyakarta, or DIY) located in
south-central Java. It is the only province in Indonesia that is still formally governed by a precolonial Sultanate, the Sultanate of Ngayogyakarta Hadiningrat. The province is divided into
five administrative districts called kabupaten, with each district divided into progressively five
smaller units beginning with subdistricts called kecamatan, and these, in turn, divided into
kelurahan, and further divided into rukun warga (RW, ca. 100-250 residences each), and
finally into rukun tetangga (RT, the smallest administrative unit composed of approximately
50 families). In addition to the city (or Kota) of Yogyakarta, D.I. Yogyakarta consists of four
additional kabupatens. Kabupatens Bantul and Sleman are located on the fluvial plains in
the south-central region and on the southern slopes of Mount Merapi in the north-central
part of the province; these two kabupatens are adjacent to and border the city to the south
and north respectively. These kabupatens are more densely populated than the kabupatens
of Kulonprogo and Gunung Kidul located in the hilly area to the east of Opak river and the
west of Progo river respectively (Figure). All five kabupatens are endemic for dengue.
In the last three decades, the Provincial Health Office and its subordinate offices within
the province have attempted to consistently follow the control recommendations of the
Indonesian Ministry of Health, with only slight local modifications. Initial efforts during
1976-1978 involved perifocal adult control using insecticide sprays through portable and
vehicle-mounted thermal fogging and ultra low volume (ULV) machines. Applications were
made at the smallest administrative level (RT) in response to a reported case of dengue
haemorrhagic fever (DHF) within a particular RW. In the 1980s, in addition to case-based
perifocal spraying, larviciding with temephos (1% sand granules applied quarterly) was
recommended in urban areas reporting DHF for three consecutive years. Since 1992, the
larval control strategy has continued and now involves community participation, health
education and intersectoral coordination. In the last decade, efforts have been focused
on empowering and organizing working groups at the kelurahan level under the general
guidance of local health centre personnel. Other efforts within the city include the activities
of the Family Welfare Education Women’s Movement (Pendidikan Kesejahteraan Keluarga or
PKK) and the promoting programme called Ten Houses (Dasa Wisma) at the neighbourhood
level, wherein residents are educated about larval inspections, water storage methods and
container cleaning to eliminate the vector. Currently, focal adulticiding using malathion or
142
Figure: Survey sites in 6 kecamatans (subdistricts) within the city of Yogyakarta,
Gedongtengen, Gondomanan, Kotagede, Mergangsan, Tegalrejo and Umbulharjo
cypermethrin (ULV and thermal fogs) in response to DHF case outbreaks are conducted
routinely by the Office of City Health Center; however, the results appear to be varied and
inconsistent. The actual impact of such a combination of control methods and strategies has
never been assessed. The situation remains one of persistent endemicity between epidemics,
with prevalence of DHF varying widely among the 45 kelurahans of the city; the vector is
certainly common in virtually all if not every neighbourhood (unpublished data from the
Yayasan Tahija Dengue Project).
Recently, a study in the city evaluated the hypothesis that a limited reduction in Ae. aegypti
adult abundance brought about by the selective treatment of particularly productive
containers would reduce dengue transmission.[3] This study was based upon earlier pupal/
demographic surveys where four classes of containers were identified for treatment; these are:
143
the bak mandi (common bathroom container); the bak air/ember (water storage container);
sumur (wells); and ban bekas (tyres).[2] The surveys and the targeted control study were
located within the single subdistrict of Gondokusuman in a 10-hectare intervention area of
lower socioeconomic, high-density housing in the city. The intervention area was compared
with a similar 10-hectare control area nearby that received no intervention except that
provided by the government. The study was monitored using backpack aspirations of adult
mosquitoes, pupal/demographic surveys and serosurveys (IgM) in children. The prevalence
of the treatment (pyriproxyfen, an insect-growth regulator) in targeted containers averaged
approximately 80%. The results indicated that the targeted intervention resulted in fewer
Ae. aegypti adults (ratio: 3.7 to 1.0) and pupae (3.7 to 1.0) when compared with the control
site. Serology indicated an average reduction in the prevalence of anti-dengue IgM in children
of 25% during the 12 months of the study; and the serosurvey associated with the 3-month
season of peak dengue transmission indicated a 61% reduction. An aggregation of dengue
cases along the periphery of the treated area suggested that movement of virus into the
treated area occurred from the surrounding untreated area.[3]
The present work extends these original pupal/demographic surveys to include other
kecamatans within the city to determine which types of containers are most important to
Ae. aegypti production and should thus be targeted in a larger city-wide targeted control
effort.
Methods
Study sites
Approximately 160 randomly-selected sites in each of six subdistricts within the City
of Yogyakarta were surveyed for Ae. aegypti adults and pupae; these sites located in
Gedongtengen, Gondomanan, Kotagede, Mergangsan, Tegalrejo and Umbulharjo (Figure).
Residential sites in the city are typically single-family homes. However, because the city has
many educational institutions, it is not uncommon for families to have student lodgers. Water
supply in the city is either from the municipal piped water system or wells. In many kelurahans
it is common to have both sources within the same house. In the residential sites, bak mandi
(BM) is a bathroom container used for bathing; another common container is the bak air
(BA) used for other needs such as cooking and dish and clothes washing. Water is stored in
BA commonly for at least three days. BMs and BAs are usually permanent containers made
of cement, with or without a ceramic finish; these containers are frequently scrubbed and
cleaned on a weekly basis (unpublished data, Yayasan Tahija Dengue Project). Occasionally,
one or more buckets (embers) are used for water storage, either for bathing or washing.
In these containers, water is commonly stored for less than one or two days and they are
cleaned after use. Wells (sumur) are a common source of water for daily living and are
built within or outside of the house; typically there are several households associated with
each well. Well water is taken either through an electric pump or is drawn manually with a
144
plastic or metal bucket. The wells vary in depth and diameter; they may be uncovered or
partially or totally covered by a cover made of wood, cement or other material. Because the
surface of the well is not accessible to an inspector, it is impossible to determine the absolute
standing crop of pupae within those surfaces; what is known is that perhaps one third of all
wells are positive for larvae and/or pupae.[4] Because pupal production in wells cannot be
quantified, the targeted control strategy developed on the basis of this survey will include
all wells as a precaution against the possibility that they are responsible for considerable
production of Ae. aegypti adults. Public and commercial sites surveyed included markets,
schools, offices, shops, mosques, etc. Typically, the city’s piped water supply is used in lieu
of wells at these sites. The water is commonly stored in BAs or plastic buckets; BMs are also
common. Because shops have a variable number of people associated with them, the surveys
did not include an entry for the number of people associated with each site; the results are
reported simply as the average number of Ae. aegypti pupae per type of container rather
than pupae per person.
Pupal/demographic surveys
Survey sites were selected using a random number generator and numbered lists of addresses
in each of the surveyed kecamatans. The pupal/demographic survey methods used in this
study were similar to that of Focks et al.[2,3] With the exception of wells, every water-holding
container, both indoors and outdoors, was examined with the aid of a flashlight for the
presence of mosquito pupae. All pupae were collected from large containers such as BMs
and BAs using a specially designed pupal suction device fitted with a flashlight; for smaller
containers, a wide-mouthed pipette was used to transfer pupae to labelled plastic collection
vials. For each container and its associated vial, a record was made indicating the type and
identification number of each container (Table 1), whether it was covered in some fashion,
its location in terms of being found indoors or out of doors, address (house ID, street, RT,
RW, and kelurahan), name of the house-owner, the number of people associated with the
site, and date. On each survey day, the vials were taken to the Entomology Laboratory of the
University of Gadjah Mada (UGM) where their contents were transferred to small emergence
cups; adults were identified to species in the case of Aedes and to genus for Culex. A total
of 960 sites were surveyed (approximately 160 sites per kecamatan).
Adult backpack aspirations
Twenty-minute aspirations for adult mosquitoes were made at each of the pupal/demographic
survey sites using battery-powered backpack aspirators.[5] The labelled collection cups (one
per site) were returned to the University of Gadjah Mada the same day where adults were
identified as in the case of pupal/demographic surveys.
145
Table 1: Controlled language names for the most common water-holding containers in
the City of Yogyakarta used in the initial surveys and pilot study;[2,3] also included are the
project-specific identification numbers (ID)
ID
146
Bahasa Indonesia
English
1
Bak air
Water container (large)
2
Bak mandi
Water container in bathroom
3
Bak sam pah
Trash can
4
Bambu
Bamboo
5
Ban bekas
Used tyres
6
Botol bekas
Used bottles
7
Drum
Drum (200 L)
8
Ember
Bucket
9
Ember plastik
Plastic bucket
10
Gayung
Dipper for water
11
Gelas bekas
Used mug/drinking glass
12
Kaleng bekas
Used tin can
13
Karpet plastik
Plastic carpet
14
Kendi
Clay water pot (small)
15
Keranjang bekas
Used basket (woven)
16
Keranjang plastik
Plastic basket
17
Kolam air
Water pool, tank, pond
18
Kolam ikan bekas
Abandoned fish pond
19
Kompor bekas
Used kerosene stove (small)
20
Mangkok plastik
Plastic bowl
21
Panci
Pan
22
Pelepah pohon
Plant axil (usually banana)
23
Penampung air kulkas
Refrigerator water pan
24
Pispot
Chamber pot
25
Pot bunga
Flower pot
26
Sepatu bekas
Used shoes
27
Sisa alat rumah tangga
Used household tools
28
Tangki air
Water tank (large)
29
Tempayan plastik
Plastic container
30
Tempayan tanah
Clay water container
31
Tempurung kelapa
Coconut shell
32
Timba bekas
Pail, bucket (used)
33
TMB
Water container for bird (small)
34
Tree hole
Tree hole
35
Vas bunga
Flower vase
36
Wood hole
Wood hole (plank)
Funnel traps
The funnel trap has been used in several countries in hard-to-access containers such as deep
wells and manholes to document whether a container is positive for mosquitoes and other
invertebrates. Because mosquito larvae are more active than pupae, most studies describe the
collection of larvae only.[6,7] A previous study in Yogyakarta using funnel traps conducted during
the dry season found Ae. aegypti larvae in more than 33% of 93 wells sampled; 4.3% had
Culex quinquefasciatus, and none were positive for Ae. albopictus (unpublished data, Yayasan
Tahija Dengue Project). In the present study, funnel traps were placed in approximately two
thirds of wells observed in the study sites and were left in situ for 24 hours.
Results
Residential sites
A total of 957 residential sites were visited for the pupal/demographic and adult surveys
(Table 2). While the mean number of people per residence was fairly uniform across the
six kecamatans studied, ranging between 4.6 and 6.4, the number of Ae. aegypti pupae
per residence was not uniform but ranged rather widely from 0.3 to 5.1. The number of
Ae. aegypti pupae per person averaged 0.37, ranging widely from 0.07 to 0.95. In the context
of developing a targeted source-reduction strategy for the city, of greater interest is the relative
and absolute contribution of different types of containers to the total production of Ae. aegypti
Table 2: Results and statistics derived from pupal/demographic surveys conducted in a
total of 957 residential sites by kecamatan (Figure); pupae here refers only to Ae. aegypti
Kecamatan
Number of
residences
surveyed
Pupal/demographic survey data (Ae. aegypti)
Number
of
people
Mean no.
of people
per
residence
Total
number
of pupae
Mean
no. of
pupae per
residence
Pupae
per
person
Gedongtengen
127
556
4.60
41
0.34
0.07
Gondomanan
100
534
5.34
506
5.06
0.95
Kotagede
179
884
4.94
279
1.56
0.32
Mergangsan
166
863
5.20
386
2.33
0.45
Tegalrejo
155
990
6.39
216
1.39
0.22
Umbulharjo
236
1,345
5.70
470
1.99
0.35
Grand Total
963
5,172
5.40
1,898
1.98
0.37
147
pupae (Table 3). The results are consistent with the original surveys in Gondokusuman, namely
that BMs and BAs are the two largest producers of Ae. aegypti pupae accounting for 75.9%
and 11.1% of all pupae respectively.[2,3] Just three types of containers, if the third largest
producer, ember (buckets)is included, account for a total of 91.1% of all pupae observed. It
is important to remember that these percentages of ‘total’ standing crop do not reflect the
unknown contribution of wells.
Table 3: Results of pupal/demographic surveys of Ae. aegypti in residential sites within
the city of Yogyakarta in 6 kecamatans. The containers are listed in order of decreasing
contribution to the total production of Ae. aegypti pupae. Only containers positive for
2 or more Ae. aegypti pupae are listed
Names
English
Bahasa
Indonesian
Bathroom
container
Bak mandi
Water
container
(large)
Total
Total
number of number of
pupae
containers
Proportion
Pupae per of pupae in Cumulative
container container proportion
type
1,465
1,169
1.253
0.759
0.759
Bak air
215
185
1.162
0.111
0.870
Bucket
Ember
79
744
0.106
0.041
0.911
Clay water
container
Tempayan
tanah
57
122
0.467
0.030
0.941
Flower pot
Pot bunga
20
35
0.571
0.010
0.968
Unused bowl
Mangkok
bekas
15
7
2.143
0.008
0.976
Pan or tray
Panci
11
1
11.000
0.006
0.981
Drip tray
dispenser
Penampung
air kulkas
11
36
0.306
0.006
0.987
Refrigerator
water pan
Penampung
air kulkas
8
31
0.258
0.004
0.991
Aquarium
Kolam ikan
7
40
0.175
0.004
0.995
Dipper
Gayung
7
1
7.000
0.004
0.998
Water
container for
bird (small)
TMB
2
132
0.015
0.001
0.999
148
The results of the 6-kecamatan survey in the city differs in two ways from the original
four surveys in Gondokusuman:[2] Firstly, virtually no Ae. albopictus pupae were collected
either in indoor or outdoor containers in this survey; in contrast, the two Gondokusuman
surveys conducted during the wet seasons of 1997 and 1999 when 281 Ae. albopictus
(virtually all outdoors) and 1862 Ae. aegypti pupae were collected during the two surveys.
Secondly, the three most productive types of containers in the earlier surveys included BM,
BA and used tyres (ban bekas). However, buckets (embers) replaced the tyres as dominant
producer in the present survey.
In contrast to the pupal/demographic surveys, Ae. albopictus and Culex spp. were
collected in the adult aspirations (Table 4). Few Ae. albopictus were collected in the adult
aspirations (average: 0.011 adults per residence) compared to Ae. aegypti (0.428) (ratio:
37.5 to 1.0). Indoor-resting Culex spp. were much more abundant than Ae. albopictus,
being found at a rate of 0.204 per house; the principal breeding sites for Culex spp. in these
residential settings are septic tanks.[3]
Finally, there does not seem to be a relationship between the average number of Ae.
aegypti pupae and adults per house as determined by backpack aspirations in residential
sites; the correlation coefficient between the averages for each of these variables was –0.144
(P=0.785).
Table 4: Results of adult aspirations in residential sites within the city of Yogyakarta in six
kecamatans. Culex spp. and Ae. aegypti adults were found in all kecamatans, however
Ae. albopictus was not found in two of the six kecamatans, Kotagede and Tegalrejo
Average number of adults per site
Kecamatan
Ae. albopictus
Ae. aegypti
Culex spp.
Totals
Gedongtengen
0.024
0.480
0.315
0.819
Gondomanan
0.010
0.490
0.040
0.540
Kotagede
0.000
0.168
0.212
0.380
Mergangsan
0.006
0.289
0.030
0.325
Tegalrejo
0.000
0.994
0.258
1.252
Umbulharjo
0.025
0.297
0.292
0.614
Averages
0.011
0.428
0.204
0.643
149
Public and/or commercial sites
The results of the pupal/demographic survey of 447 public sites in the city (Table 5) indicate
that there was approximately one-half the diversity in the types of containers present in the
public sites. These surveys did not record the number of people per site as this was variable.
The results were consistent with the original surveys in Gondokusuman and the residential
surveys (above), namely, that BMs, BAs and ember (buckets) were the three largest producers
of Ae. aegypti pupae accounting for 61.6%, 10.7%, and 13.8% of all pupae (total 86.1%)
respectively. If the four most productive types of containers are taken into consideration (the
fourth largest producer was flower pots (pot bunga) (3.1%), a total of 89.3% of all pupae
can be accounted for.
Table 5: Results and statistics derived from pupal/demographic surveys conducted in
public sites by kecamatan (Figure); pupae here refers only to Ae. aegypti
Names
English
Bahasa
Indonesian
Total
Total
number of number of
pupae
containers
Proportion
Pupae per of pupae in Cumulative
container container proportion
type
Bathroom
container
Bak mandi
258
991
0.260
0.616
0.616
Bucket
Ember
58
342
0.170
0.138
0.754
Water container Bak air
(large)
45
207
0.217
0.107
0.862
Flower pot
Pot bunga
13
36
0.361
0.031
0.893
Pan or tray
Panci
12
1
12.000
0.029
0.921
Gravestone
Nisan
10
25
0.400
0.024
0.945
Piring
Plate
8
1
8.000
0.019
0.964
Flower vase
Vas bunga
6
12
0.500
0.014
0.979
Fish pond
Kolam ikan
5
21
0.238
0.012
0.991
Clay water
container
Tempayan
tanah
4
11
0.364
0.010
1.000
150
Funnel traps
There was total of 347 wells in the study sites of the six kecamatans surveyed; of these, 220
were examined with funnel traps for mosquito pupae. Aedes aegypti pupae were recovered
only from the wells in Umbulharjo (9 pupae in 3 wells) and Kotagede (23 pupae in 6 wells); no
other species were observed. In these nine collections, the most common number of pupae
recovered was one; on single occasions the counts were 2, 3, 7 and 15 per collection.
Discussion
These results indicate that a targeted strategy involving the containers BM, BA and buckets
would address 91.1% and 86.2% of all Ae. aegypti production in the above-ground-level
containers in residential and commercial sites respectively. As in the case of the pilot study,
wells could be a fourth type of container included in a targeted control strategy because we
know wells produce Ae. aegypti, although we cannot quantify their contribution.[3]
While funnel traps are normally not efficient in collecting mosquito pupae, the numbers
of pupae collected on two occasions, 7 and 15 from individual wells in a single day, is a
worrisome reminder that we do not have an adequate knowledge regarding well productivity
in Yogyakarta. In the present study, only 9 out of 220 wells sampled were positive for pupae
(4.1%). This brings out the fact that the contribution of adult mosquitoes from wells may negate
the successful targeting of only the surface containers to suppress dengue transmission
We do not have an explanation for the lack of a correlation between the numbers of adults
and pupae in houses in Yogyakarta but note that this has been observed elsewhere.[8]
Cryptic breeding of dengue vectors has been the surprising finding of several control
attempts and the existence of cryptic breeding cannot be ruled out in this study.[9,10,11]
Acknowledgements
We would like to thank and acknowledge the significant contributions of Dr Sjakon Tahija
and Mr George Tahija of the Tahija Foundation, Jakarta, who fully supported this work. We
are also grateful to the staff of the Faculty of Medicine, University of Gadjah Mada (UGM),
Yogyakarta, for their support. We thank Mr Heru Sudibyo, Department of Parasitology,
UGM, and his entomology surveyor team who dedicated considerable time in the field
and laboratory during the conduct of this study. We are most appreciative of the support
and contributions of the Health Agency of the City of Yogyakarta. And, finally, we gratefully
acknowledge Mr Titayanto Pieter (Program Manager) and Ms Sukma Tin Aprillya (Dengue
Project Manager) of Tahija Foundation for their many significant contributions in logistics,
implementation, management and communications.
151
References
[1] Suroso T, Holani A, Ali I. Dengue Haemorrhagic Fever Outbreaks in Indonesia 1997-1998. WHOSEARO Dengue Bulletin. 1998; (22):45-48.
[2] Focks DA, Bangs MJ, Church C, Juffrie M, Nalim S. Transmission thresholds and pupal/demographic
surveys in Yogyakarta, Indonesia for developing a dengue control strategy based on targeting
epidemiologically significant types of water-holding containers. Dengue Bulletin. 2007; (31): 83-102.
[3] Focks DA, Juffrie M, Umniyati SR, Nalim S, Laksono IS, Intansari US, Satoto TBT, Titayanto P, Soeripto
N. Pilot evaluation of a targeted source control strategy designed to reduce dengue transmission in
Yogyakarta, Indonesia. PLoS Negl Trop Dis (submitted September 2011).
[4] Gionar YR, Rusmiarto S, Susapto D, Bangs MJ. Use of a funnel trap for collecting immature Aedes
aegypti and copepods from deep wells in Yogyakarta, Indonesia. Journal of the American Mosquito
Control Association. 1999: 15(4):576-80.
[5] Clark GG, Seda H, Gubler DJ. Use of the “CDC backpack aspirator” for surveillance of Aedes aegypti in
San Juan, Puerto Rico. Journal of the American Mosquito Control Association. 1994; 10(1): 119-124.
[6] Kay BH, Cabral CP, Araujo DB, Ribeiro ZM, Braga PH, Sleigh AC. Evaluation of a funnel trap for
collecting copepods and immature mosquitoes from wells. Journal of the American Mosquito Control
Association. 1992; 8(4): 372-5.
[7] Russell BM, Kay BH. Calibrated funnel trap for quantifying mosquito (Diptera: Culicidae) abundance
in wells. Journal of Medical Entomology. 1999; 36(6): 851-5.
[8] Garcia-Rejon J, Loroño-Pino MA, Farfan-Ale JA, Flores-Flores L, Del Pilar Rosado-Paredes E, RiveroCardenas N, Najera-Vazquez R, Gomez-Carro S, Lira-Zumbardo V, Gonzalez-Martinez P, LozanoFuentes S, Elizondo-Quiroga D, Beaty BJ, Eisen L. Dengue virus-infected Aedes aegypti in the home
environment. American Journal of Tropical Medicine and Hygiene. 2008; 79(6): 940-50.
[9] Barrera R, Amador M, Diaz A, Smith J, Munoz-Jordan JL, Rosario Y. Unusual productivity of Aedes
aegypti in septic tanks and its implications for dengue control. Medical and Veterinary Entomology.
2008; 22(1): 62-9.
[10] Gonzalez R, Suarez MF. Sewers: the principal Aedes aegypti breeding sites in Cali, Colombia. American
Journal of Tropical Medicine and Hygiene. 1995; 53: 160.
[11] Kay BH, Ryan PA, Russell BM, Holt JS, Lyons SA, Foley PN. The importance of subterranean mosquito
habitat to arbovirus vector control strategies in north Queensland. Australian Journal of Medical
Entomology. 2000; 3: 846 – 853.
152
Ovitrap surveillance of dengue and chikungunya
vectors in several suburban residential areas
in Peninsular Malaysia
Lim Kwee Wee,a Norzahira Raduan,a Sing Kong Wah,a Wong Hong Ming,a
Chew Hwai Shi,a Firdaus Rambli,a Cheryl Jacyln Ahok,a Nazni Wasi Ahmad,a
Lee Han Lim,a# Andrew McKemeyb & Seshadri Vasanb,c
a
Medical Entomology Unit, Institute for Medical Research, Jalan Pahang, 50588 Kuala Lumpur,
Malaysia.
b
c
Oxitec Limited, 71 Milton Park OX14 4RX, UK.
University of Malaya, CEBAR, IPS Building (Level 5, Block B), 50603 Kuala Lumpur, Malaysia.
Abstract
Ovitrap surveillance was conducted in six suburban residential areas in Peninsular Malaysia in 2008.
Aedes albopictus was found to be the most abundant Aedes species at all study sites, even though
a small number of Aedes aegypti was found in two residential areas. This study also reconfirmed
that Ae. albopictus prefers to breed in outdoor conditions, while Ae. aegypti prefers indoors. There
is no evidence of a change in their breeding preferences, possibly due to the existence of a stable
ecosystem at the study sites.
Keywords: : Ovitrap surveillance; Aedes aegypti; Aedes albopictus; Malaysia.
Introduction
Dengue and chikungunya are endemic in Malaysia. Aedes aegypti is the primary vector of
dengue, while Aedes albopictus is likely to be the major vector of chikungunya.[1] These
diseases are found mainly in the urban and suburban areas.[2]
Because of global warming, Ae. aegypti and Ae. albopictus may extend their range
northward and southward and have more rapid metamorphosis.[3] Increasing road transport and
urbanization and introduction of tap water supply, normally irregular and intermittent, helps
create a friendly environment for the establishment of the vector species in new areas.[4] Today,
an estimated 3.46–3.61 billion people live in areas at risk of dengue in 134 countries, which
#
E-mail: [email protected]; Telefax: +60326162688
153
Ovitrap surveillance of dengue and chikungunya vectors in Peninsular Malaysia
corresponds to 53.0%–55.0% of the world population; WHO expects that millions more will
be affected in the coming years.[5-6] Besides dengue infection, chikungunya is another Aedes
mosquito-borne infection which is rapidly emerging in many Indian Ocean countries.[4,7]
In Malaysia, the incidence rate of dengue has increased fivefold from 28 cases per
100 000 people in 1995 to 133 cases per 100 000 people in 2004.[8] During 2002–2007, the
immediate cost of dengue to Malaysia was US$88–215 million per annum, which translates
to US$3.5–8.5 per capita and accounts for 3%–7% of the government spending on health
care. Illness costs due to dengue are typically 11 times the government spending on Aedes
vector control. Increased investments in prevention could potentially generate large offsets
in illness costs.[9]
An improved understanding of Aedes population dynamics would probably lead to more
effective vector control to combat dengue and chikungunya in Malaysia, although other nonvector factors such as climate change are also important considerations in vector control. Thus,
the objective of this study was to determine the distribution and abundance of both Ae. aegypti
and Ae. albopictus in several suburban residential areas in Peninsular Malaysia.
Study sites
Ovitrap surveillance was conducted in six residential areas: Taman Karak Jaya (Pahang),
Taman Bukit Tinggi (Pahang), Taman Angsamas (Negeri Sembilan), Taman Sri Ramai (Negeri
Sembilan), Taman Inang Sari (Malacca) and Taman Krubong Permai (Malacca). The ecological
description of the study sites is given in Table 1.
Table 1: Ecological description of study sites in Peninsular Malaysia
Study site
Ecological description
GPS coordinates
Taman Karak Jaya
• 150 single- or double-storey houses
• Some houses scattered around
N 03° 25.364’
E 102° 01.589’
Taman Bukit Tinggi
• Mixture of brick houses and wooden houses
N 03° 21.311’
E 101° 49.005’
Taman Angsamas
• Houses made of cement and bricks
N 02° 38.891’
E 101° 55.453’
Taman Sri Ramai
N 02° 37.838’
E 101° 57.140’
Taman Inang Sari
• 200 single-storey houses
N 02° 20.032’
E 102° 15.057’
Taman Krubong
Permai
• 250 single-storey houses
N 02° 18.654’
E 102° 15.076’
154
All the six sites are within 3–25 km of the town centres and have good infrastructure
and excellent access to all means of communication. These are suburban areas surrounded
by forest, oil palm or rubber plantation. Almost all houses have ornamental plants or fruit
trees in front and flower pots inside.
Ovitrap surveillance
The ovitrap surveillance, as described by Lee,[10] was conducted by adhering to the guidelines
of the Ministry of Health, Malaysia.[11] A black plastic container of 300 ml volume, with a
base diameter of 6.5 cm, opening diameter of 7.8 cm and 9.0 cm in height, was used as an
ovitrap container. Hardboard measuring 10 cm x 2.5 cm x 0.3 cm was used as an oviposition
paddle. The paddle was placed in the ovitrap container with the rough surface kept upwards
and tap water added to a level of 5.5 cm.
Ovitraps were placed indoors and outdoors in randomly selected houses scattered
over each study area (Table 2). Indoors refers to the interior of the house and outdoors is
the outside of the built-up area but still within the immediate boundary of the house.[10] All
the traps were labelled and placed near potential resting sites which were not flooded or
exposed to direct sunlight. The average temperature in Malaysia in June 2008 was 33 °C
and from September to December 2008 it was 22 °C.
Table 2: Number of ovitraps placed in the study sites and date of ovitrapping,
Peninsular Malaysia
Study site
Number of ovitrap
Date of ovitrapping
Taman Karak Jaya
20 indoors
20 outdoors
11 Jun 2008 to 18 Jun 2008
Taman Bukit Tinggi
20 indoors
20 outdoors
12 Jun 2008 to 19 Jun 2008
Taman Angsamas
30 indoors
30 outdoors
13 Nov 2008 to 20 Nov 2008
Taman Sri Ramai
30 indoors
30 outdoors
12 Nov 2008 to 19 Nov 2008
Taman Inang Sari
20 indoors
20 outdoors
10 Sep 2008 to 17 Sep 2008
Taman Krubong Permai
30 indoors
30 outdoors
3 Dec 2008 to 10 Dec 2008
Ovitraps were collected after seven days and the contents were transferred into plastic
containers (16 cm x 11 cm x 7 cm). Fish food (Tetramine®) was provided as larval food. Since
there is no diapause or overwintering in Malaysian mosquitoes, hatching of eggs will not
be influenced. All the hatched larvae were counted and identified at third or fourth instar
under a compound microscope.
155
Data analysis
The ovitrap result was expressed as ovitrap index and larval density (no. of larvae per trap)
as follows:
Ovitrap Index (OI) = (Number of positive traps / Number of recovered traps) x 100%
Mean number of larvae per trap = Total number of larvae / Number of recovered ovitraps
All levels of statistical significance were determined at p<0.05 by using independent
t- test and the statistical programme SPSS v10.
Results
A total of 40 to 60 ovitraps were randomly placed indoors and outdoors in selected houses
and 90%–100% of the ovitraps were recovered from each site.
Figure 1 shows the ovitrap index of Ae. aegypti and Ae. albopictus at the six study sites.
The highest ovitrap index of Ae. albopictus (71%) was found in Taman Bukit Tinggi while
Taman Krubong Permai had the lowest ovitrap index of Ae. albopictus (45%). Ae. aegypti was
found in Taman Angsamas and Taman Inang Sari with a very low ovitrap index, i.e. 2% and 5%
respectively. The presence of Ae. aegypti at other sites was considered negligible. The results
revealed that Ae. albopictus was the predominant Aedes species in all the six study sites.
Figure 1: Comparative ovitrap index of Ae. aegypti and Ae albopictus in six study sites in
Peninsular Malaysia
156
Taman Bukit Tinggi also showed the highest mean number of Ae. albopictus in both
indoors and outdoors compared to the lower mean number of Ae. albopictus in Taman
Krubong Permai (Table 3). Although the outdoors mean number of larvae per trap was higher
than indoors mean number of larvae per trap for Ae. albopictus in all six study sites (Figure 2),
there was no significant difference (p>0.05), except for Taman Sri Ramai (p<0.05).
Table 3: Overall indoors and outdoors mean numbers of larvae per trap of Ae. albopictus
and Ae. aegypti in six study sites in Peninsular Malaysia
Study site
Mean number of larvae per trap of Ae. albopictus and Ae. aegypti
Overall
Indoors
Outdoors
Tmn Karak Jaya
17.47 ± 23.10
15.72 ± 22.37
19.05 ± 24.21
Tmn Bukit Tinggi
38.93 ± 41.09
26.45 ± 37.59
51.40 ± 41.53
Tmn Angsamas
23.82 ± 27.02
(0.02 ± 0.13)
17.82 ± 23.49
(0.04 ± 0.19)
29.62 ± 29.29
(0)
Tmn Sri Ramai
16.33 ± 18.56
9.60 ± 15.56
23.07 ± 19.11
Tmn Krubong Permai
9.78 ± 14.43
6.37 ± 15.21
13.20 ± 12.97
Tmn Inang Sari
20.84 ± 23.68
(2.62 ± 12.05)
14.58 ± 25.77
(1.79 ± 7.80)
26.80 ± 20.38
(3.40 ± 15.20)
Figure 2: Comparison of mean numbers of larvae per trap of Ae. albopictus indoors and
outdoors in six study sites in Peninsular Malaysia (Error Bar = Standard Error Mean =
Standard Deviation/n)
157
Discussion
Ae. albopictus was predominant in all the six study sites. This was similarly reported by
Norzahira et al.,[12] Rozilawati et al.,[13] Chen et al.[14] and Sallehudin et al.[15] in the surveys
done in rural and suburban areas in Peninsular Malaysia. According to Braks et al.,[16] WHO,[17]
Foo et al.[18] and Sucharit et al.,[19] the habits of Ae. aegypti and Ae albopictus mosquitoes
are different. Ae. aegypti prefers urban areas with less vegetation, rests in dark, humid and
secluded places inside houses or buildings, biting indoors and breeding in artificial containers,
while Ae. albopictus is found commonly in rural areas with vegetation, biting outdoors and
breeding in all types of natural and artificial containers.
Ae. albopictus is native to south-east Asia.[20] Macdonald[21] reported that Ae. aegypti
had been introduced into Malaysia through the seaport and coastal areas at the beginning
of the 20th century, while Ae. albopictus is undoubtedly common near the forest fringes and
in the interior of secondary forest.[22] As all the six study sites are located near to forest, oil
palm and rubber plantation which are the common habitat environment of Ae. albopictus,
it is possible that Ae. albopictus had spread to and remained in the study sites.
Only Ae. albopictusi was found in Taman Karak Jaya, Taman Bukit Tinggi, Taman Sri Ramai
and Taman Krubong Permai, possibly because Aedes mosquitoes increased their numbers by
colonizing of available sites rather than moving into previously uninfested areas.[23]
Rozilawati et al.[13] and Chen et al.[14] also found that Ae. albopictus preferred to breed
outdoors rather than indoors in Taman Permai Indah, Penang and Kampung Baru, Kuala
Lumpur. The breeding sites of Ae. albopictus are not only around and near houses but also in
forests and plantations. Unlike Ae. aegypti which bites and rests indoors, Ae. albopictus bites
both outdoors and indoors and rests mainly outdoors.[24] This may explain the preference of
Ae. albopictus to breed outdoors rather than indoors.
In conclusion, data acquired from this ovitrap surveillance is useful in the planning of
anti-Aedes campaign such as Communication for Behavioural Impact (COMBI), insecticide
application and use of other new technologies for vector control. COMBI includes a variety
of activities such as marketing, education, communication promotion, advocacy and
mobilization intended to engage individuals in considering recommended healthy behaviours
and to encourage the adoption and sustained maintenance of these behaviours.[25] Insecticides
can be applied to mosquito breeding sites and houses, and use of personal repellents can
reduce the incidence of insect bites and thus infection.[26] Application of new technology such
as genetic-based strategies to prevent Aedes mosquitoes from transmitting dengue viruses
either by reducing the densities of mosquito populations or by eliminating their ability to
transmit dengue viruses can be considered.[27] Information obtained from this study provides
important entomological data for the design of an effective integrated dengue vector control
programme.
158
Acknowledgements
The authors thank the Director-General of Health, Malaysia, for permission to publish this
paper. Thanks are also due to the Director of Institute for Medical Research and the staff of
the Medical Entomology Unit, IMR, Kuala Lumpur, for their support and help. This study was
supported by the National Institutes of Health, Ministry of Health, Malaysia, under research
grant No. JPP-IMR-06-053.
References
[1] Reiter P, Fontenille D, Paupy C. Aedes albopictus as an epidemic vector of chikungunya virus: another
emerging problem? The Lancet. 2006; 6: 463-464.
[2] Chen CD, Seleena B, Masri SM, Chiang YF, Lee HL, Nazni WA, Sofian-Azirun M. Dengue vector
surveillance in urban residential settlement areas in Selangor, Malaysia. Trop Biomed. 2005; 22(1):
39-43.
[3] Shope R. Global climate change and infectious diseases. Env Health Persp. 1991; 96: 171-174.
[4] Mourya DT, Yadav P. Vector biology of dengue and chikungunya viruses. Indian J Med Res. 2006; 124:
475-480.
[5] Beatty MR, Letson W, Edgil DM, Margolis HS. Estimating the total world population at risk for locally
acquired dengue infection. 50th ASTMH Meeting 2007. http://www.pdvi.org/PDFs/Estimating_the_
population_at_risk_for_locally_acquired_dengue.pdf - accessed on 26th February 2008.
[6] Mahr K. Vagobond virus: dengue fever is spreading and some think climate change is to blame. Time.
2007 December. p.38.
[7] World Health Organization. Chikungunya in La Réunion Island (France) 2006. Geneva: WHO, 2006.
http://www.who.int/csr/don/2006_02_17a/en/ - accessed 12 January 2012.
[8] Kumarasamy R. Dengue fever in Malaysia: time for review? Med J Malaysia. 2006; 61(1): 1-3.
[9] Lee HL, Vasan SS, Birgelen L, Murtola TM, Gong HF, Field RW, Mavalankar DV, Nazni WA, Lokman
HS, Shahnaz M, Ng CW, Lum LCS, Suaya JA, Shepard DS. Immediate cost of dengue to Malaysia and
Thailand: an estimate. Den Bull. 2010; 14: 65-76.
[10] Lee HL. Aedes ovitrap and larval survey in several suburban communities in Selangor, Malaysia. Mosq
Borne Dis Bull. 1992; 9(1): 9-15.
[11] Tee AS, Daud AR, Alias M, Lee HL, Tham AS. Guidelines on the use of ovitrap for Aedes surveillance.
Vector control Unit, Vector-borne Disease section, Ministry of Health, Malaysia 1997, 6 pages.
[12] Norzahira R, Hidayatulfathi O, Wong HM, Cheryl A, Firdaus R, Chew HS, Lim KW, Sing KW, Mahathavan
M, Nazni WA, Lee HL, Vasan SS, McKemey A, Lacroix R. Ovitrap surveillance of the dengue vectors,
Aedes (Stegomyia) aegypti (L.) and Aedes (Stegomyia) albopictus Skuse in selected areas in Bentong,
Pahang, Malaysia. Trop Biomed. 2011; 28(1): 48-54.
[13] Rozilawati H, Zairi J, Adanan CR. Seasonal abundance of Aedes albopictus in selected urban and
suburban areas in Penang, Malaysia. Trop Biomed. 2007; 24(1): 83-94.
159
[14] Chen CD, Seleena B, Nazni WA, Lee HL, Masri SM, Chiang YF, Sofian-Azirun M. Dengue vectors
surveillance in Endemic Areas in Kuala Lumpur City Centre and Selangor State, Malaysia. Den Bull.
2006; 30: 197-203.
[15] Sallehudin S, Zainol AP, Jeffery J, Ismail G, Busparani V. Studies on the distribution and abundance of
Aedes aegypti (L.) and Aedes albopictus (Skuse) (Diptera: Culicidae) in an endemic area of dengue/
dengue haemorrhagic fever in Kuala Lumpur. Mosq Borne Dis Bull.1991; 8(2): 35-39.
[16] Braks MAH, Honorio NA, Lourenco-de-Oliveira R, Juliano SA, Lounibos LP. Convergent habitat
segregation of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in Southeastern Brazil and
Florida. J Med Entom. 2003; 40(6): 785-794.
[17] World Health Organization, Regional Office for South-East Asia. Prevention and control of dengue and
haemorrhagic fever: comprehensive guidelines. New Delhi: WHO-SEARO, 1999. pp 49-51.
[18] Foo LC, Lim WT, Lee HL, Fang R. Rainfall, abundance of Aedes aegypti and dengue infection in Selangor,
Malaysia. Southeast Asian J Trop Med Public Health. 1985; 16(4): 560-568.
[19] Sucharit S, Tumrasvin W, Vutikes S, Viraboonchai S. Interactions between larvae of Ae. aegypti and
Ae. albopictus in mixed experimental population. Southeast Asian J Trop Med Public health. 1978; 9:
93-97.
[20] Delatte H, Dehecq JS, Thiria J, Domerg C, Paupy C, Fontenille D. Geographic distribution and
development sites of Aedes albopictus (Diptera: Culicidae) during a chikungunya epidemic event. Vec
Borne Zoo Dis. 2008; 8(1): 25-34.
[21] MacDonald WW. Aedes aegypti in Malaya, I. Distribution and dispersal. Ann Trop Med Parasitot. 1956;
50: 385-398.
[22] MacDonald WW. An interim review of the non-anopheline mosquitoes of Malaya. Stud Inst Med Res.
1957; 28: 1.
[23] Stickman D, Kittayapong P. Dengue and its vectors in Thailand: Introduction to the study and seasonal
distribution of Aedes larvae. Am J Trop Med Hyg. 2002; 67(3): 247-259.
[24] Cheong WH. Preferred Aedes aegypti larval habitats in urban areas. Bull World Health Organ. 1967;
36: 586-589.
[25] Parks W, Lloyd L. Planning social mobilization and communication for dengue fever prevention and
control: a step-by-step guide. Geneva: World Health Organization, 2004. pp 6-12.
[26] WHO. Pesticides and their application for the control of vectors and pests of public health importance
2006 (114 pages). Geneva: World Health Organization.
[27] McCall PJ, Kittayapong P. Control of dengue vector: tools and strategies. Scientific Working Group:
Report on Dengue. Geneva: WHO, 2006. pp. 110-118.
160
Specifying skills for proficient control of Aedes aegypti
oviposition in flowerpot saucers through the use of net
covers
João Bosco Jardim,# Ana Carolina Bocewicz & Virgínia Torres Schall
Laboratory of Health and Environmental Education, René Rachou Research Center,
Fundação Oswaldo Cruz (Fiocruz Minas), Belo Horizonte, MG, Brazil.
Abstract
Net covers have been used as physical barriers to prevent oviposition by the dengue vector Aedes
aegypti into water-bearing containers. However, their efficacy as a prevention tool depends upon
the proficiency (correctness) with which they are used. In the first part of this paper we describe the
method by which a pattern of skills for the proficient use of a kind of net cover for flowerpot saucers
(evidengue®) was empirically specified into verbal descriptions, or categories. After identifying by
direct video observation a set of key-skills to meet predetermined specifications of the proficiency
of the use of the evidengue®, we specified these skills in four categories of proficiency. In the
second part of the paper we describe the procedure and the results of an experimental evaluation
which aimed at measuring the extent to which the skills specified in the categories were performed
by four groups of high school students, after an educational practice on dengue prevention in
classroom. The evaluation compared two skills instruction procedures for the proficient use of
evidengue®. In one of the procedures the skills were explicitly instructed through a video and/or
leaflet in three experimental groups. In the other, the skills were not explicitly instructed. Trained
observers independently recorded the frequency of the categories. The inter-observer agreement
indices obtained show that the measurement of the frequencies of three of the four categories was
reliable. In the inter-group comparison, the evaluation showed that the group that was submitted
to explicit instruction of the skills through video and leaflet yielded relatively higher frequency of
categories of proficiency than the others. Studies such as the one we present here make it possible
to create reliable indicators of proper use of resources aimed at prevention of oviposition and
consequent control of Ae. aegypti breeding at the household level.
Keywords: Aedes aegypti; Net cover; Skills; Proficiency of use; Flowerpot saucer; Dengue prevention;
Health education.
#
161
Proficient control of Aedes aegypti using net covers
Introduction
The most basic way of dengue vector control takes place in the household and depends on
the residents’ behaviour, notwithstanding the importance of infrastructure actions. It consists
in the mere expedient of blocking the access of gravid female Aedes aegypti mosquitoes, the
main urban vector of the disease, to the interior of storage tanks, buckets, flowerpot saucers
and other kinds of domestic containers in which there is exposed and standing water.[1] Ideally,
this action on the part of the residents will prevent the ovipositioning and the consequent
development of the mosquito in the water.
Mosquito-proof net covers have been employed as physical barriers to prevent the
ovipositing Ae. aegypti access to the interior of water-bearing domestic containers. One kind
of cover (evidengue®) can seal off flowerpot saucers in such a way so as to confer complete
protection against vector oviposition in these containers, which are frequently positive in
south-eastern Brazil. Evidengue® has been shown to be 100% efficacious in preliminary
laboratory evaluations.[2,3] However, as it happens with other kinds of mosquito-proof net
covers,[4–8] its efficacy as a prevention tool depends upon the proficiency (correctness) of
its use.[3,9] It is only by sealing the container that a resident can proficiently block vector
access to its interior. The act of sealing is, thus, more proficient (in the sense of being more
efficacious as preventive behaviour) than the mere use of lids, which often leave gaps for
gravid female Ae. aegypti to enter and lay eggs inside the container.[10] When used with
proficiency, evidengue® can be characterized as a sealing cover for controlling Ae. aegypti
oviposition in flowerpot saucers.
Health education programmes routinely emphasize the importance of proficiency in
using several kinds of prevention tools. Male condom is a case in point. One function of the
condom is to prevent the spread of sexually transmitted diseases. But certain behavioural skills
are needed to use it proficiently as non-proficient use may well prevent it from fulfilling such
a function. This means to abide by some predetermined specifications. Briefly, the condom
needs to be placed on the erect penis, then slipped integrally on to the member, squeezed
at the tip to leave space for semen to collect, and so on. By the same token, the use of a
net cover, to be proficient, must abide by its corresponding predetermined specifications.
Operationally, such specifications constitute verbal descriptions of some pattern of behavioural
skills that a resident must perform to seal off a water-bearing container proficiently.
The use of net covers for dengue prevention in households should of course be a part
of integrated, community-based vector control measures.[11] But however much is known
about the necessary sanitation measures for vector control at the household level,[11,12] it is
surprising that little attention has been paid to the specification of behavioural skills required
from residents for putting these measures into practice proficiently. Our own experience with
evidengue® has shown[13] that a certain proportion of people are deficient in various skills
to meet with proficiency a request for placing the cover on a flowerpot saucer, no matter
162
how simple this behaviour may be. Moreover, the design of a cover itself may not match
the user’s skills to place it on a container proficiently.
As in other scientific endeavours based on preventive behaviours (for instance, breast selfexamination,[14,15] firearm injury prevention,[16] bicycle helmet use,[17] etc.), a health education
programme intending to involve residents in dengue vector control by using mosquito-proof
net covers needs to consider the prior specification of these skills in a practical and objective
way.* Developing a cover to prevent Ae. aegypti oviposition in domestic containers is one
thing, but specifying behavioural skills ensuring its proper use by residents is quite another.
As stated by Elder and Lloyd,[22] social mobilization efforts for dengue prevention may take
different forms depending on whether their recipients provide evidence or not of the skills
to engage in vector control. It is our contention that a vector control initiative involving the
employment of net covers in households must specify those skills empirically through research
of the proficiency of use of its particular kind of cover by prospective residents.
Such a specification of skills with respect to the proficient use of evidengue ® was
the object of the present study. Its aim was twofold. First, to describe a method through
which a pattern of skills for the proficient use of this particular cover can be specified into
a catalogue[23] of verbal descriptions, or categories, of proficiency; second, to evaluate the
catalogue experimentally in order to measure the extent to which the skills specified in the
various categories are performed by prospective users, after an educational practice on
dengue prevention.
Evidengue®
Structurally, evidengue® consists of a circular arrangement of synthetic polyester resin
mosquito net, with mesh equal to or smaller than 2 mm x 1 mm.[2,3] Its sac-shaped design
makes it possible for it to wrap the saucer and, at the same time, a portion of the flowerpot
walls up to a height distant from the water. The cover has a frill along the aperture brim
through which two straps of the same polyester material are embedded and, internally, there
is also a rubber band. The straps have the function of firmly adjusting the aperture of the
cover to the flowerpot so as not to leave any gaps for the passage of the vector, while the
rubber band helps keep the edge of the cover adjusted and away from the water.
* We note that the term ‘skill’ is not employed here in the sense of an inner, inherited talent which would predispose
an individual to behave in a predetermined manner. Rather, it is used in the sense of a specific ability or a particular
dexterity that may be instructed, acquired and displayed by the individual in important situations.[18] In this acceptation, skill and proficiency are equivalent concepts. It draws on the empirical research literature from the psychology
discipline that calls itself behaviour analysis.[19--21]
163
Specification of skills and catalogue of categories of proficiency
The table presents an overview of the study design. Drawing on the literature about direct
observation of human and animal behaviour,[23-28] the specification of the behavioural skills
for the proficient use of evidengue® started with the observation, in a video, of a sequence of
cover manipulation movements vis-à-vis its placement on a set of saucer and flowerpot. This
sequence was taken as reference pattern for the identification and posterior specification of
the skills. It was extracted from a 70-second domestic video produced in order to demonstrate
the proficient placement of evidengue® on a flowerpot in a previous study.[3,29] The systematic
observation of this sequence made it possible to: (a) identify a pattern of four key-skills for
the proficient use of the cover; and (b) specify these skills in verbal descriptions (categories)
of use proficiency (hereafter called categories of proficiency).
Table: Overview of the study design
(1) Skills identification
(a) Video observation of cover manipulation
(b) Identification of key-skills (after a total of 22 skills identified)
(2) Categorization
(a) Gradual specification of key-skills in verbal descriptions or categories of proficiency
(b) Filmed individual tests of categories
(c) Repeated observation of filmed performances, rectification and adjustment of
categories
(d) Final specification of key-skills into a catalogue of categories of proficiency
(3) Experimental catalogue evaluation
(a) Educational practice (two instruction procedures, with and without explicit instruction
of proficiency)
(b) Demonstration and recording
The following key-skills were identified: (i) full insertion of the saucer and flowerpot into
the cover; (ii) pulling the opening edge upwards so as to keep the rubber band suspended
at a height of the flowerpot that is sufficiently distant from the water inside the saucer;
(iii) contour flowerpot wall with the adjusting straps; (iv) making of a knot with the straps tight
against the flowerpot wall. From a total of 22 skills identified in the video, these four were
considered essential for compliance with the predetermined use proficiency specifications
of the evidengue®.
Once identified through direct video observation, the skills started to be gradually
specified in categories of proficiency. In many sessions held over several days, the categories
were taken to individual tests with 57 voluntary participants (age range 15–76 years). In these
164
sessions, the participants were instructed by one of the researchers to place evidengue® on a
flowerpot saucer. The instruction was given in conformity with the video’s original sequence
and the specifications of each tested category. The sessions were filmed. Eventually, through
repeated observations of the participants’ performances, the categories were successively
rectified, and terms were added, substituted and suppressed until a catalogue was compiled
and afterwards evaluated (see below).
The categories that constituted the catalogue were the following, in this sequence:
•
Insertion: open evidengue®, position the saucer and the flowerpot at the cover’s
wrong side, totally fitting the flowerpot base inside the saucer.
•
Pulling: elevate the edge of evidengue® to a height that reaches the higher half of
the flowerpot, without reaching the aperture.
•
Contour: surround evidengue® with the polyester straps, in opposing directions, at
the height of the rubber band, and bring them close.
•
Knot: cross the straps and knot them close to the flowerpot’s wall, stretching the
straps to their maximum, in opposing directions.
Catalogue evaluation
The catalogue evaluation compared the relative frequency of occurrence of the categories
of proficiency (dependent measure) in two instruction procedures for the use of the cover.
In one of them, the proficiency was explicitly instructed according to the various categories,
whereas in the other (control), the proficiency was not explicitly instructed. The procedures
were carried out in a classroom during an educational practice of dengue prevention with
high school students. Prior to the study, ethical clearance was granted from the Ethics
Committee of René Rachou Research Center and informed consent was obtained from all
participants.
The evaluation was based on the frequency records of the categories obtained in a
demonstration session of the placing of evidengue® on flowerpot saucers, carried out by
students immediately after an educational practice. The participants were 96 students from
both sexes (age range 16–31 years), gathered into four classes (1 to 4) of a public school in
a dengue-endemic district in the city of Belo Horizonte, Minas Gerais state, Brazil.
The instruction procedures followed an experimental design composed by three
components: lecture on dengue (LD), delivery of a leaflet (LF) instructing how to seal a
flowerpot saucer using evidengue®, and exhibition of a video (VI) about the correct way of
placing the cover on the saucer. The components were differentially associated in classes
2, 3 and 4 (hereafter called experimental groups), whereas class 1 was considered control
group. The modalities of association were as follows: Group 2: LD+LF (N = 22); Group 3:
LD+VI (N = 30); Group 4: LD+LF+VI (N = 22). In Group 1 (LD), N was 22.
165
Lecture on dengue: Adapted from a previous study,[29] the 8-minute lecture was given
by one of the members of the present study’s team (second author). It succinctly comprised
six topics related to dengue: (i) concept of dengue; (ii) symptoms of the disease; (iii) forms
of clinical manifestation; (iv) transmission; (v) life-cycle of Ae. aegypti; and (vi) prevention.
Pictures related to these topics were projected onto a screen through 28 PowerPoint colour
slides. Though seven of the slides showed illustration photos of covered and uncovered
flowerpot saucers, including a saucer sealed with evidengue®, no explicit instruction was
given in the lecture in connection with the proficiency in the use of the cover.
Leaflet and video: The proficiency was explicitly instructed in print (leaflet) and electronic
(video) media. In the leaflet, the categories were represented by colourful photos, with
legends in conformity with the specifications of the skills in the catalogue. In two imperative
sentences, the leaflet highlighted the importance of sealing with evidengue® and asked the
student to follow a sequence of steps (numbered in the legends) to seal the flowerpot saucer
with the cover. In the 52-second, mute, coloured semi-professional video, the categories
were converted into moving images. In it, the instructor showed the proficient placing of
evidengue® on to a flowerpot and saucer set similar to the one that was subsequently used in
the demonstration through which the catalogue was evaluated. In addition to the key-skills,
four skills considered non-essential were added to the leaflet and video: taking evidengue®
off its package, stretching the cover’s aperture before insertion, placing the saucer separately
(before) the flowerpot, and tying a bow with the straps after the knot.
Demonstration: The demonstration was carried out individually, immediately after the
educational practice. Two benches from a science laboratory contiguous to the classroom
were used. Each bench had a violet flowerpot with its respective saucer and a plastic package
containing one evidengue® in a size that corresponded to the saucer’s dimensions. Each
student received oral instruction, individually, from the instructor, about the demonstration,
at the bench. The instruction followed a standard text. The students from Groups 2 and 4
could freely consult the leaflet they received in the educational practice. The demonstration
started with the removal of the evidengue® from its package. After each demonstration was
concluded, the respective student exited the laboratory and the remaining students, who
waited in the classroom, were successively called by the instructor for demonstration on
one bench or the other.
Two pairs of previously trained observers, one at each bench, recorded independently,
in a paper-and-pencil observation form, the frequency of the occurrence of each of the four
categories in the catalogue. The educational practice and the demonstration were carried
out in a single morning during school hours, following a predetermined sequence for the
four groups.
Results: We calculated the inter-observer agreement (IOA) index in order to estimate
the reliability of the records in each pair. Reliability concerns the extent to which a given
measurement is consistent and repeatable.[27] In the present study, the IOA index was
166
expressed as the percentage of all occurrences of a given category about which the two
observers of each pair have agreed, i.e. Agreements/(Agreements+Disagreements) x 100.
This index is widely used in behavioural observation studies[30-33] and is particularly suited
to nominal or categorical measures.[23] We also calculated the kappa correlation coefficients
in each pair.
In the whole set of records, the IOA index of pair 1 was smaller (87.5%) than the index
of pair 2 (97.9%). When calculated separately for each category of proficiency, the indices of
pair 1 were smaller for pulling (79%), contour (83%), and knot (81%), whereas the insertion
index was the same (100%) in both pairs. All the kappa values for both overall and individual
categories were inferior to 0.05. Taken together, these results indicated that the measurement
of the frequencies of the categories insertion, contour and knot was consistent and repeatable.
The pulling index in pair 1 was relatively low and did not allow for this conclusion.
The figure shows the relative frequency of the categories of proficiency in each of
the four groups. In the inter-groups comparison, the relative frequency of the categories
insertion and knot was consistently higher (minimum of 86.7% for insertion in Group 3) than
of the categories pulling and contour. Pulling was the less frequent category (minimum of
40.9% in Group 1). The difference between the relative frequencies of the four categories
Figure: Relative frequency of the categories of proficiency in each of the four groups
167
of proficiency of the four groups was statistically significant (Cochran-Mantel-Haenszel test,
p-value <0.05). Group 4 produced more categories of proficiency. The average relative
frequency of categories was as follows: Group 1 (LD) = 71.6%; Group 2 (LD+LF) = 78.4%;
Group 3 (LD+VI) = 76.7%; Group 4 (LD+LF+VI) = 88.6%.
Discussion
Although some researchers have called attention to the need for taking into account the
behavioural skills of participants in the initiatives for dengue prevention at the household
level,[12,34] as of now, no research seems to have sought to specify empirically the skills
necessary for residents to prevent proficiently Ae. aegypti breeding in domestic water
containers.
The present method of specifying skills for the proficient use of evidengue® was conducted
in a way similar to a procedure for developing a task analysis.[35] Quite often a task analysis
begins with a broad scope and uses the information gathered during its development to
narrow its focus. This is generally a laborious task, which requires numerous observations
and rectifications. In this study, the method involved the preliminary breaking down of a
previously recorded sequence of cover manipulation movements into 22 skills. It is worthy
of the attention of researchers and practitioners engaged in dengue health education that,
in the end, the catalogue of categories of proficiency comprised a small proportion (18.2%)
of these skills. That is to say, only a few behavioural skills appear to be the underlying
determinants of the proficient use of evidengue®. Field studies on the efficacy of the cover’s
use might test this conjecture.
The method described here becomes more significant for health educators as we move
from evidengue® to other kinds of net covers that can be employed in vector control initiatives.
The generality of the method has of course to be demonstrated, but it looks as if its main
features may well be extended to other kinds of covers. These features can be summarized
as follows: (a) the empirical identification of a pattern of essential skills for compliance
with predetermined proficiency specifications in the use of a cover; (b) the specification of
the essential skills in terms of verbal categories of use proficiency; and (c) the test and, if
necessary, the concomitant refining of these categories so as to obtain a set that will compose
a catalogue for posterior use.
Mosquito-proof net covers are prevention tools designed to be a hindrance or obstacle to
the egg stage of Ae. aegypti life-cycle. Several kinds of covers now exist, yet their employment,
even when insecticide-treated,[7,36] is somewhat unsystematic and thus their efficaciousness
is still questionable.[7,10] In general terms, this is a problem related to the skills of the people
(residents or others) using the cover. But however much the users are heterogeneous in their
skills, this may be a problem also related to the design itself of a given kind of cover. In the
present study with evidengue®, the catalogue evaluation showed that pulling and contour
168
were the categories less frequently performed in all four groups. The relative frequency of
pulling, in particular, was specially low in Groups 1 and 3. A behavioural skill deficit can be
remediated by training,[18] but if one knows beforehand that the proficient use of a cover
requires a skill that is performed with a frequency so low by a sample of potential users,
the problem should probably be addressed by changing the design of the cover, not the
behaviour of the user.
Evidengue® is still being developed, and although previous evaluations have shown its
efficacy in the laboratory, the current study pointed out the need for a structural change. For
one part, the contour has been eliminated in a new design that does not require the knot,
substituting it with a sliding acrylic lock, which brings the polyester strips together in parallel
and adjusts them firmly to the flowerpot, at the same height of the rubber band, thereby
sealing the saucer with a proficiency probably greater than the one previously obtained with
the knot. On the other hand, the pulling, as specified in the catalogue, became unnecessary,
since the elevation of the edge of the evidengue® may now be carried out through the
movement of the lock to the required height. The new behavioural skills resulting from the
change still need to be evaluated.
It should be noted that the IOA index of the pulling category remained below 80%,
which is the lower edge of the range of acceptability of the majority of studies that use direct
observation in educational, clinical and other settings.[23,26,37] Thus, in addition to a likely skill
deficit[22] or an inadequate design, we cannot exclude the possibility that the low frequency of
pulling was also related to some deficiency in the verbal description of this skill. Still another
possibility is an insufficiency in the training of observers.[23,26]
We are not aware of any procedure or measure that has associated school education to
the proficiency in the use of a net cover to prevent Ae. aegypti oviposition in water-bearing
containers in households. Proficiency involves behavioural skills that can be dealt with
quantitatively, as shown in the present study. We measured the frequency of occurrence of a
set of categories of proficiency for placing evidengue® in flowerpot saucers after a classroom
educational practice, and found that a procedure in which the proficiency is explicitly
instructed through leaflet and video (i.e. showing through these means how a container
should be sealed) results in substantially higher proficiency indices than a procedure in
which the proficiency is not explicitly instructed. In other words, our evaluation suggests
that without the explicit instruction of how to use proficiently a net cover, students may not
acquire sufficient skills to achieve the proficiency required for vector control with this device
at the household level.** This topic needs investigation.
** It is, in short, a variation of the theoretical question of distinguishing the learning which involves words from the
learning which involves actions,[38] something that has been addressed, in the case of dengue prevention, in terms of a
“know-do gap”[39].
169
It should be stressed that the explicit instruction and the instruction media (leaflet and
video) were not mutually exclusive. A study interested in determining the differential influence
of one or another of these factors should employ a design which allows manipulating them
independently. In this event, it might be specially interesting to investigate the specific
influence of the leaflet, whose modalities of association in Groups 2 and 4 (LD+LF and
LD+LF+VI) yielded relatively higher frequency of categories of proficiency than the modality
of Group 3 (LD+VI).
The study of proficiency through behavioural science methods can open up research lines
to other prevention fields, such as insecticide-treated bednets for malaria control,[40] where
the literature has shown frequent inadequacies and protection failures. Also, behavioural
methods can be employed in asthma cases in which simple technologies are often used in
a non-proficient way by patients and professionals.[41]
Acknowledgement
This study was supported by a research grant from Fapemig (APQ 1738-5.01/07) and
CNPq.
References
[1] Morrison AC, Zielinski-Gutierrez E, Scott TW, Rosenberg R. Defining challenges and proposing solutions
for control of the virus vector Aedes aegypti. PLoS Med. 2008; 5: e68.
[2] Schall VT, Barros HS, Jardim JB, Secundino NFC, Pimenta PFP. Dengue prevention at the household
level: Preliminary evaluation of a mesh cover for flowerpot saucers. Rev Saude Publica. 2009; 43:
895-897.
[3] Jardim JB, Barros HS, Gonçalves CM, Pimenta PFP, Schall VT. The control of Aedes aegypti for water
access in households: Case studies towards a school-based education programme through the use of
net covers. Dengue Bull. 2009; 33: 176-186.
[4] Kittayapong P, Strickman D. Three simple devices for preventing development of Aedes aegypti larvae
in water jars. Am J Trop Med Hyg. 1993; 49:158-165.
[5] Socheat D, Chantha N, Setha T, Hoyer S, Chang MS, Nathan MB. The development and testing of
water storage jar covers in Cambodia. Dengue Bull. 2004; 28:8-12.
[6] Seng CM, Setha T, Nealon J, Chanta N, Socheat D, Nathan MB. The effect of long-lasting insecticidal
water container covers on field populations of Ae. aegypti (L.) mosquitoes in Cambodia. J Vector Ecol.
2008; 33: 333-341.
[7] Chuang HY, Huang JJ, Huang YC, Liu PL, Chiu YW, Wang MC. The use of fine nets to prevent the
breeding of mosquitoes on dry farmland in southern Taiwan. Acta Trop. 2009; 110: 35-37
170
[8] Kittayapong P, Chansang U, Chansang C, Bhumiratana A. Community participation and appropriate
technologies for dengue vector control at transmission foci in Thailand. J Amer Mosq Cont Assoc.
2006; 22: 538-546.
[9] Jardim JB, Schall VT. Dengue prevention: Focus on proficiency. Cad. Saude Publica. 2009; 25:25292530.
[10] Strickman D. Laboratory demonstration of oviposition by Aedes aegypti (Diptera: Culicidae) in covered
water jars. J Med Entomol. 1993; 30:947-949.
[11] Renganathan E, Parks W, Lloyd L, Nathan MB, Hosein E, Odugleh A, Clark GG, Gubler DJ, Prasittisuk
C, Palmer K, San Martin J-L. Towards sustaining behavioural impact in dengue prevention and control.
Dengue Bull. 2003; 27: 6-12.
[12] McCall PJ, Kittayapong P. Control of dengue vectors: Tools and strategies. Scientific Working Group,
Report on Dengue. Working paper 6.2. Geneva: World Health Organization, Special Programme for
Research and Training in Tropical Diseases, 2007.
[13] Bocewicz ACD. Um modelo experimental (evidengue®) para o desenvolvimento de tecnologia de
instrução de proficiência na área da saúde. Belo Horizonte, 2009. (http://is.gd/Xk62Vn - accessed 12
Jan 2012).
[14] Pennypacker HS, Iwata MM. MammaCare: A case history in behavioural medicine. In: Blackman DE,
Lejeune H eds. Behaviour analysis in theory and practice: Contributions and controversies. Hove, East
Sussex: Lawrence Erlbaum, 1990.
[15] Saunders KJ, Pilgrim CA, Pennypacker HS. Increased proficiency of search in breast self-examination.
Cancer. 1986; 58: 2531-2537.
[16] Miltenberger RG, Flessner C, Gatheridge B, Johnson B, Satterlund M, Egemo, K. Evaluation of behavioral
skills training to prevent gun play in children. J Appl Behav Anal. 2004; 37: 513-516.
[17] Van Houten R, Van Routen J, Malenfant JEL. Impact of a comprehensive safety program on bicycle
helmet use among middle-school children. J Appl Behav Anal. 2007; 40: 239-247.
[18] O’Donohue W, Ferguson KC, Pasquale M. Psychological skills training: Issues and controversies. Behav
Anal Today. 2003; 4:331-335.
[19] ABAI. Association for Behavior Analysis International. http://www.abainternational.org/ - accessed 13
Jan 2012.
[20] Blackman DE, Lejeune H eds. Behaviour analysis in theory and practice: Contributions and controversies.
Hove, East Sussex: Lawrence Erlbaum, 1990.
[21] Lattal KA, Chase PN. Behavior theory and philosophy. New York: Plenum, 2003.
[22] Elder J, Lloyd LS. Achieving behaviour change for dengue control: Methods, scaling-up, and sustainability.
In: World Health Organization. Report of the Scientific Working Group meeting on dengue, Geneva,
1-5 Oct 2006. Geneva: WHO, 2007. pp 140-149. (http://is.gd/1o2Ny2 - accessed 12 Jan 2012).
[23] Martin P, Bateson P. Measuring behaviour: An introductory guide. 2nd edn. Cambridge: Cambridge
University Press, 1993.
[24] Hutt SJ, Hutt C. Direct observation and measurement of behavior. Springfield IL: Charles C Thomas,
1970.
171
[25] Bijou SW, Peterson RF, Ault MH. A method to integrate descriptive and experimental field studies at
the level of data and empirical concepts. J Appl Behav Anal. 1968; 1:175-91.
[26] Hartman DP. Using observers to study behavior. San Francisco: Jossey-Bass, 1982.
[27] Hartman DP, Wood DD. Observational methods. In: Bellack AS, Hersen M, Kazdin AE eds. International
handbook of behavior modification and therapy. New York: Plenum, 1982.
[28] Thompson T, Symons FJ, Felce D. Behavioral observation. Baltimore: Paul H. Brooks, 2000.
[29] Barros HS. Investigação de conhecimentos sobre a dengue e do índice de adoção de um recurso
preventivo (capa evidengue®) no domicílio de estudantes, associados a uma ação educativa em ambiente
escolar. Rio de Janeiro: Instituto Oswaldo Cruz, 2007.
[30] Williams JH, Geller ES. Behavior-based intervention for occupational safety: Critical impact of social
comparison feedback. J Safety Res. 2000; 31:135-142.
[31] Hanley GP, Cammilleri AP, Tiger JH, Ingvarsson ET. A method for describing preschoolers’ activity
preferences. J Appl Behav Anal. 2007; 40: 603-618.
[32] Iwata BA, Pace GM, Kissel RC, Nau PA, Farber JM. The self-injury trauma (SIT) scale: A method for
quantifying surface tissue damage caused by self-injurious behavior. J Appl Behav Anal. 1990; 23:
99-110.
[33] Kent RN, O’leary DK, Dietz A, Diament C. Comparison of observational recordings in vivo, via mirror,
and via television. J Appl Behav Anal. 1979; 12:517-522.
[34] Winch PJ, Leontsini E, Rigau-Pérez, JG, Ruiz-Pérez M, Clark GG, Gubler DJ. Community-based
dengue prevention programs in Puerto Rico: Impact on knowledge, behavior, and residential mosquito
infestation. Am J Trop Med Hyg. 2002; 67:363-370.
[35] Sulzer-Azaroff B, Reese EP. Applying behavior analysis: A program for developing professional competence.
New York: Holt, Rinehart & Winston, 1982.
[36] Kroeger A, Lenhart A, Ochoa M, Villegas E, Levy M, Alexander N, McCall PJ. Effective control of dengue
vectors with curtains and water container covers treated with insecticide in Mexico and Venezuela:
Cluster randomized trials. BMJ. 2006; 392: 1247-1252.
[37] Bailey JS, Burch MR. Research methods in applied behavior analysis. Thousand Oaks: Sage, 2002.
[38] Catania AC. Learning. Englewood Cliffs: Prentice Hall, 1998.
[39] World Health Organization. Bridging the “know–do” gap: meeting on knowledge translation in global
health. Geneva: WHO, 2006.
[40] Kroeger A, Mancheno M, Alarcon J, Pesse K. Insecticide-impregnated bed nets for malaria control:
Varying experiences from Ecuador, Colombia, and Peru concerning acceptability and effectiveness.
Am J Trop Med Hyg. 1995; 53: 313-323.
[41] Frade JCQP. Avaliação de conhecimentos, habilidades e atitudes de farmacêuticos inseridos em um
Projeto de Educação em Saúde relativo à asma. Belo Horizonte MG: Centro de Pesquisas René Rachou,
2006. (http://is.gd/hfWQ88 - accessed 12 Jan 2012).
172
Evaluation of Mesocyclops aspericornis,
Mesocyclops ogunnus and Mesocyclops
thermocyclopoides from the water bodies of
Chennai (south India) as control agents of Aedes aegypti
Zehra Amtuz# & Nasarin A.
Post-Graduate and Research Department of Zoology,
Justice Basheer Ahmed Sayeed (JBAS) College for Women, Chennai 600 018, India.
Abstract
The predatory capacity of cyclopoid copepods was considered for use as a biological control
agent for Aedes aegypti larvae. Experiments were conducted in 1-litre beaker by introducing
Aedes aegypti larvae at densities of 25, 50 and 100. Experiments were also carried out in 100-litre
trough in field and laboratory to ascertain the efficiency of Mesocyclops aspericornis to predate
on mosquito larvae. The predation rate was lower in the field-simulated experiment than in the
laboratory. Experiment to find the efficiency of Mesocyclops aspericornis to predate on mosquito
larvae throughout its lifespan was carried out. The efficacy of Ceriodaphnia cornuta and copepod
(M. aspericornis, M. ogunnus and M. thermocyclopoides) in controlling immature forms of Aedes
aegypti was also assessed.
Keywords: Aedes aegypti; Mesocyclops aspericornis; Mesocyclops ogunnus; Mesocyclops thermocyclopoides;
South India.
Introduction
Mosquito control in India has become problematic. Mosquitogenic conditions are growing
due to large-scale developmental activities. Control efforts are directed toward decimating
the populations of vector mosquitoes which transmit deadly and debilitating diseases such
as malaria, filariasis, Japanese encephalitis and dengue and dengue haemorrhagic fever
(DHF).
Dengue and dengue haemorrhagic fever (DF/DHF) are mosquito-borne viral diseases
known to occur in more than 100 countries, placing two fifths of the world’s population
#
173
Evaluation of Mesocyclops for control of Aedes aegypti immatures in Chennai
at risk.[1,2] The increased transmission and geographical spread of DF and its more severe
form – DHF makes it the most important mosquito-borne viral disease of humans (50–100
million infections/year). Aedes aegypti, the urban yellow fever mosquito, is the principal
dengue-carrying vector. In India, DF/DHF is hyper endemic.
Along with the other methods of control, such as chemical and environmental control,
biological control can be classified as naturalistic control, which is a broad term for the control
of mosquito larvae by predation.
Genus Mesocyclops is one of the most important genera of Cyclopoida utilized for the
control of Aedes aegypti larvae. Mesocyclops species can effectively reduce the number of
Aedes aegypti larvae in both laboratory and natural settings.[3] Various species of Mesocyclops,
Macrocyclops, Megacyclops and Acanthocyclops have been tested in a variety of Aedes
breeding habitats[4,5,6] with promising results. One of the important factors influencing
the efficacy of the use of Mesocyclops to control mosquito larvae is its ability to subsist in
containers regularly used by people.[6,7]
The importance of naturalistic measures in the control of Aedes aegypti has been well
emphasized in recent years.[8,9] One of the best methods of successfully combating mosquitoes
on an extensive scale could be the biological control methods.
The predacious cyclopoid copepods, Mesocyclops sp, are known for their predatory
effects on mosquito larvae. However, so far, no investigations on the predatory ability of
M. asperiornis, M. ogunnus and M. thermocyclopoides have been carried out in Chennai
(south India). A preliminary attempt has been made to obtain baseline data to assess the
potential of this predator for possible use in the control of dengue vector in Chennai.
Zooplanklon samples were collected from the freshwater fish pond of the Hydrobiological
Research Station, Tamil Nadu State Fisheries Department, Chetpet, Chennai.
The cyclopoids used in the study were Mesocyclops aspericornis, Mesocyclops ogunnus
and Mesocyclops thermocyclopoides and these were identified based on the morphological
and taxonomic key characters provided by Van de Velde (1984)[10], Dussart and Defaye
(1995)[11] and Zehra and Altaff (2002).[12]
Mesocyclops aspericornis, Mesocyclops ogunnus and Mesocyclops thermocyclopoides
were made to predate on different densities of mosquito larvae (1st instar Aedes aegypti
larvae) and their efficacy was assessed. Eggs used in the laboratory study were obtained from
a susceptible colony of Aedes aegypti maintained at the Vector Control Research Centre,
Puducherry, south India.
174
The experiment was initiated by combining a single female Mesocyclops aspericorns with
different larval densities of 1st instar Aedes aegypti larvae (25, 50, 100) in troughs of 25-litre
capacity. The predation rate was assessed at the end of 24 hours. Similar experiment was
carried out for M. ogunnus and M. thermocyclopoides.
M. aspericornis and M. ogunnus were inoculated in 100-litre troughs with larval density
of 1000. The experiment was conducted in laboratory and field in order to assess the efficacy
of Mesocyclops species to predate in two different environmental conditions.
The mosquito larvae for the field trials were established from the wild – field-caught
mosquitoes. Twenty ovitraps were placed around the college campus. In order to establish
mosquito eggs, hay was introduced in a beaker containing water for 24-48 hrs, which
promoted the production of microbes. The water from the beaker was introduced in flat
black trays. Filter papers were placed partially immersed in water for the oviposition of the
mosquitoes. The troughs used for the field experiment were covered with fine mesh net to
prevent contamination from other organisms. Larvae and pupae of mosquito and all stages
of copepods (nauplii and adults) were sampled at the end of the experiment.
The efficiency of M. aspericornis to predate on mosquito larvae in the presence of an
alternate prey (Ceriodaphnia cornuta) was assessed by introducing three larval densities
(25, 50, 100). The number of larvae and C. cornuta consumed by M. aspericornis was
evaluated.
In order to assess the feeding or predatory habit of M. aspericornis during its entire
life span, experiments were carried out for 45 days, 6th copepodid stage of M. aspericornis
was introduced and 100 larvae per day were inoculated in 1-litre beaker. The efficiency of
M. aspericornis to predate on mosquito larvae was evaluated at the end of every fortnight.
All the experiments were carried out five times.
Results and discussion
In the laboratory, tests were carried out in 1-litre beakers by introducing Aedes aegypti 1st instar
larvae at densities of 25, 50 and 100, by keeping the number of Mesocyclops aspericornis.
Mesocyclops ogunnus and Mesocyclops thermocyclopoides constant for 24 hours (Table 1).
M. aspericornis showed excellent predatory efficiency by producing a consumption rate of
90%–100%.
A comparative study between M. aspericornis and M. ogunnus was done in the laboratory
as well as in the field stimulated experiment in 100-litre troughs (Table 2). The results showed
that the predation rate was lower in the field-stimulated experiment than in the laboratory,
a decrease of production rate by 5%. A similar study was carried out in Brazil where, under
175
Table 1: Predation of M. aspericornis, M. ogunnus and M. thermocyclopoides on three
Ae. aegypti 1st instar larval densities for 24 hours
Cyclopoids
M. aspericornis
M. ogunnus
M. thermocyclopoides
1+25
1+50
1+100
*22–25
**23.8a ± 0.58
40–46
42.2b ± 1.35
80–90
83c ± 2.54
20–23
21.6 ± 0.59
30–35
32.6 ± 0.53
40–45
41.4 ± 0.97
10–12
11 ± 0.44
17–20
19 ± 0.51
30–35
31.4 ± 0.97
*Range
**Mean ± Standard error
a
No. of larvae consumed by M. aspericornis in 1±25 combination is significant when compared to M. ogunnus and M.
thermocyclopoides.
b
No. of larvae consumed by M. aspericornis in 1±50 combination is significant when compared to the M. ogunnus
and M. thermocyclopoides.
c
No. of larvae consumed by M. aspericornis in 1±100 combination is significant when compared to the M. ogunnus
and M. thermocyclopoides.
Table 2: Predation of M. aspericornis and M. ogunnus on Aedes aegypti larvae in
laboratory and field for one week
Combination
1+1000
M. aspericornis
M. ogunnus
Lab
Field
Lab
Field
*700–822a
**700.4 ± 21.21
450–558
504.0 ± 17.56
300–370b
334.60 ± 12.04
199–250
219.00 ± 9.41
*Range
a
Total no. of larvae consumed by M. aspericornis in laboratory is significant when compared to field.
b
Total no. of larvae consumed by M. ogunnus in laboratory is significant when compared to field.
laboratory conditions, four different strains of M. aspericornis showed the potential for
biological control. In Viet Nam, under laboratory conditions, M. aspericornis consumed a
mean of 23.75 L and killed a mean of 13.43 within 24 hours, while M. ogunnus consumed
a mean of 8.481 and killed a mean of 7.54.
The results of similar stimulated field experiments carried out in Thailand showed that
M. thermocyclopoides could not completely eliminate all daily-inoculated larvae. But the
results of cage-stimulated experiments conducted by Kay et al. (1992),[5] Jennings et al.
(1995)[13] and Schaper (1999)[14] showed that M. guangxiesis and M. aspericorns eliminated
all mosquito larvae produced by 25 pairs of Aedes aegypti in 3-litre tins placed in screen
176
cages that were inoculated by 50 gravid female cyclopoids six weeks after the start of the
experiment.[13] Fifty copepods each of M. longuisetus and M. aspericornis killed all Aedes
aegypti larvae in 15-litre earthenware pots placed in cages within three weeks.[5] The
difference between the results of the present study and those of related studies is due to
the larger size of the container and large volume of water (100 litres) which we used in
our experiment. In such a large volume of water, the frequency of encounter between the
predator and the prey is greatly reduced. In small-sized containers with a small volume of
water, the chance of encounter is high. To compensate for the level of reduced encounters,
it will be desirable to stock large numbers of predators, or augment the number of predators
by timely inoculations.
Moreover, reduction in the predatory rate of M. aspericornis and M. ogunnus in field
trials is more when compared to laboratory trials because, in natural environment, the water
is likely to be contaminated with microorganisms like protozoa and algae.
The efficiency of M. aspericornis to feed on mosquito larvae and cladoceran (Ceriodaphania
cornuta) is shown in Table 3. The number of larvae consumed by M. aspericornis for
combination of 1+25 ranged between 22–25 (23.8 mean), for 1+50 combination it ranged
between 40–46 (42.2 mean), and for 1+100 combination the number ranged between
80–90 (83 mean), while the number of Ceriodaphaia cornuta consumed by M. aspericornis for
combination of 1+25 ranged between 10–14 (11.58 mean), for 1+50 combination it ranged
between 15–20 (16.4 mean) and for 1+100 combination it ranged between 20–25 (21.6
mean). However, our study showed that the presence of an alternative prey (Ceriodaphnia,
cornuta) did not in any way affect the efficiency of predation on Aedes aegypti larvae,
indicating its preference for 1st instar Aedes aegypti larvae. Similar laboratory experiments were
evaluated by Ramkumar and Ramakrishna (2002)[15] using Mesocyclops thermocyclopoides.
Table 3: Predation of M. aspericornis on Aedes aegypti larvae and
Ceriodaphnia cornuta for 24 hours
Aedes aegypti
Ceriodaphnia cornuta
1+25
1+50
1+100
*22–25
**23.8a ± 0.58
40–46
42.2b ± 1.35
80–90
83.00c ± 2.54
10–14
12.00 ± 0.70
15–20
16.40 ± 0.97
20–25
21.600 ± 0.927
*Range
a
No. of larvae consumed by M. aspericornis in 1+25 combination is significant when compared to the C. cornuta
consumed.
b
consumed.
c
consumed.
177
Larval Aedes aegypti survivorship in the containers with Mesocyclops sp, was significantly
lower than in the control containers. Furthermore, the Aedes aegypti mortality was higher
in those containers with a higher Mesocyclops sp. density. Similar results were obtained by
Micieli et al. (2002)[16] in laboratory bioassays.
The potential efficiency of M. aspericornis to predate on mosquito larvae throughout
the lifespan is shown in Table 4.
Table 4: Predation of M. aspericornis on Aedes aegypti larvae during its lifespan
M. aspericornis
1+100
1–15
16–30
31–45
*1200–1350
**1277.8a ± 30.99
850–900
872.0 ± 8.60
400–450
435.60 ± 9.42
*Range
a
No. of larvae consumed by M. aspericornis during the first and second phases is significant when compared to
3rd phase.
The incidence of larval mortality caused by M. aspericornis during the 1st phase (1-15 days)
ranged between 1200–1300 (1277.8 mean), for 2nd phase (16-30 days) it ranged between
850–900 (872 mean) and for 3rd phase (31-45 days) it ranged between 400–450 (435.6
mean). The efficacy of predation on mosquito larvae is the highest during the initial adult
phase of the life-cycle of the Mesocyclops species. M. aspericornis showed an excellent
predation rate during the first fortnight; and the predation rate decreased in the second and
third phases. This is due to senescence, which results in reduced metabolic activities during
the final stages of its life-cycle. The peak levels of predation on larvae at the initial stage of
an adult indicate the need for food for its growth and development, as the larvae are found
to be rich in lipid content required for the development of the egg sac.[17]
The successful predatory effect of Mesocyclops species, especially M. aspericornis, on
Aedes aegypti larvae has been observed mainly in laboratory experiments.[18] It has been
observed that Mesocyclops sp. reduces the larvae population of Aedes aegypti by more than
99%, which has encouraged the use of Mesocyclops species as a routine test in mosquito
larvae control programmes.[19]
Mesocyclops species are the most promising biological control option for use against
Aedes aegypti, being particularly efficient in containers.[20] During recent years, Mesocyclops
species has become the focus of attention for the biological control of mosquito larvae
mainly because of its voraciousness as a predator and its survival capacity.[21] In addition,
Mesocyclops species offers the advantage of being established in cultures relatively easily
and at low cost,[20] being compatible with some of the insecticides used in the larval control
of mosquitoes and being feasible to deliver with conventional equipment.[22,23]
178
However, the effectiveness of M. aspericornis as a biological agent of mosquito control
rests in its ability to survive in containers during the oviposition period of Aedes aegypti.[12]
Mesocyclops aspericornis showed a high potential for efficacy as a biological control
agent for Aedes aegypti in the present study. Though ecological and social limitations suggest
the effectiveness of Mesocyclops species as a means of biological control of Aedes aegypti, it
has been argued that any method, whether mechanical or biological, has to be undertaken
with full community participation. Local population will have to be provided the necessary
technical information about the method being adopted and their support sought in order
to make the effort effective.[13]
Acknowledgement
The authors are grateful to the management of the Justice Basheer Ahmed Sayeed College
for Women, Chennai, for providing facilities to carry out this work. The authors also thank
immensely Dr Tran Vu Phong, Department of Vector Ecology and Environment, Institute
of Tropical Medicine, Nagasaki University, Nagasaki, Japan, for his critical review of the
manuscript.
References
[1] World Health Organization. Dengue Guidelines for diagnosis, treatment, prevention and control.
Geneva: WHO, 2009.
[2] Whitehorn J, Farrar J. Dengue. Br Med Bull. 2010; 95: 161-173.
[3] Hurlbut HS. Copepod observed preying on first instar larva of Anopheles quadrimaculatus. J Parasitol.
1938; 24: 281.
[4] Riviere F, Thirel R. ‘La predation du copepods Mesocyclops leuckarti pilosa sur les larves de Aedes
(Stegomyia) aegypti et Ae. (St.) polynesiensis essais preliminaires d’utilization comme de lutte biologique’,
Entomophaga. 1981; 26: 427–439.
[5] Kay BH, Cabral CP, Sleigh AC, Brown MD, Ribeirio ZM, Vasconcelos AW. Laboratory evaluation of
Brazilian Mesocyclops (Copepoda: Cyclopidae) for mosquito control. Journal of Medical Entomology.
1992; 29, 599-602.
[6] Marten GG, Borjas G, Cush M, Fernandez E, Reid JW. Control of larval Aedes aegypti in peridomestic
breeding containers. J Med Entomol. 1994; 31: 36-44.
[7] Vu SN, Nguyen TY, Kay BH, Marten GG, Reid JW. Eradication of Aedes aegypti from a village in Vietnam,
using copepods and community participation. Am J Trop Med Hyg. 1998; 594(4): 657-660.
[8] Micieli MV, Marti G, García JJ. Laboratory evaluation of Mesocyclops annulatus (Wierzejski, 1892)
(Copepoda: Cyclopidea) as a predator of container-breeding mosquitoes in Argentina. Mem Inst
Oswaldo Cruz, Rio de Janeiro. 2002; 97(6): 835-838.
179
[9] Raheel U, Faheem M, Riaz MN, Kanwal N, Javed F, Zaidi NS, Qadri I. Dengue fever in the Indian
subcontinent: an overview. J Infect Dev Ctries. 2011; 5(4): 239-247.
[10] Van de Velde, L. Revision of the African species of the genus Mesocyclops (Sars, 1914) (Copepoda :
Cyclopoida). Hydrobiologia. 1984; 109: 3-66.
[11] Dussart BH, Defaye D. Copepoda. Intoduction to the copepoda. 1995; 7: 1-253.
[12] Amtuz Z, Altaff K. Redescription of Mesocyclops aspericornis (Daday, 1906) (Copepoda: Cyclopoida)
from an Indian pond. J Plankt Res. 2002; 24(5): 481-493.
[13] Jennings CD, Phommasak, B, Sourignadeth B, Kay BH. Aedes aegypti control in the Lao People’s
Democratic Republic, with reference 5T to copepods. Am J Trop Med Hyg. 1995; 53: 324-330.
[14] Schaper S. Evaluation of Costa Rican copepods (Crustacea: Eudecapoda) for larval Aedes aegypti
control with special reference to Mesocyclops thermocyclopoides. J. Am. Mosq. Contr. Assoc. 1999;
15: 510-519.
[15] Ramkumar T, Ramakrishna Rao. Journal of predation on mosquito larvae by Mesocyclops
thermocyclopoides (Copepoda: Cyclopoide) in the presence of alternate prey. New Delhi: Department
of Zoology, University of Delhi, 2002.
[16] Micieli MV, Marti G, Garcia JJ. Laboratory evaluation of Mesocyclops annulatus (Wierzenjski, 1892)
(Copepoda: Cyclopoidea) as a predator of containers breeding mosquitoes in Argentina. Mem Inst
Oswaldo Cruz. 2002; 97: 835-838.
[17] Zehra Amtuz, Altaff K, Mating, Spermatophore transport and reproductive potentiality of Mesocyclops
aspericornis (Copepoda: Cyclopoida). Canadian Journal of Zoology. (In Press). 2010.
[18] Brown MD, Kay BH, Hendrikz JK. Evaluation of Australian Mesocyclops (Copepoda: Cyclopoida) for
mosquito control. J Med Entomol. 1991; 28: 618-623.
[19] Marten GG, Bordes ES, Mieu N. Use of cyclopoid copepods for mosquito control. Hydrobiologia.
1994; 293: 491-496.
[20] Suarez MF, Clark GG. Mass cultivation of copepods used for the biocontrol of Aedes aegypti. J Am
Mosq Control Assoc. 1992; 6: 314-315.
[21] Urbano LS, Andrade CFS, Carvalho GA. Biological control of Aedes albopictus (Diptera : Culicidae)
larvae in trap tyres by Mesocyclops longisetus (Copepoda : Cyclopidae) in two field trials. Memories
do Instituto Oswaldo Cruz. 1996; 91: 161-162.
[22] Marten G, Crush M, Fernandez E, Borjas G, Protillo H. Mesocyclops longisetus and other forms of
biological control for Aedes aegypti larvae in the integrated dengue control project, El Progreso, Honduras.
Dengue. A World-wide problem, a common strategy (ed. by S.B. Halstead and H. Gomez-Dantes),
133-137. New York: Ministry of Health, Mexico and Rockfeller Foundation, 1993.
[23] Nam VS, Nguyen TY, Tran VP, Truong UN, Le QM, Le VL, Elimination of dengue by community
programs using Mesocyclops (Copepoda) against Aedes aegypti in central Vietnam. Am J Trop Med
Hyg. 2005; 72: 67-73.
180
Misting of Bacillus thuringiensis israelensis (Bti) to
control Aedes albopictus in an industrial area –
the Singapore experience
S. Dulangi M. Sumanadasa,a Caleb Lee,a Sai Gek Lam-Phua,a Deng Lu,a
Lee-Pei Chiang,a Sin-Ying Koou,a Cheong-Huat Tan,a Sook-Cheng Pang,a
Nasir Maideen,b Lee-Ching Nga# & Indra Vythilingama
Environmental Health Institute, National Environment Agency, 11 Biopolis Way #06-05/08, Helios
Block, Singapore 138667.
a
Southwest Regional Office, Sunset Way, Clementi, Singapore.
b
Abstract
The objective of this study was to determine the residual efficacy of Bacillus thuringiensis israelensis
(Bti) misting against Aedes albopictus in an industrial area in Singapore. Pre- and post-treatment
ovitraping were carried out before and after Bti misting. In order to determine residual efficacy,
wet and dry cups were placed randomly in the treated area during misting, and one hour later,
Ae. albopictus larvae (L3) were introduced and mortality was recorded 24 hours later. Larvae
were introduced into the same cups on a weekly basis. Residual effects of Bti treatment at various
distances and under different environmental conditions were also observed. There were no
significant differences in egg counts from ovitraps among all the three sites before treatment. Bti
misting resulted in a significant reduction in egg counts in all the three sites. The residual action
of Bti was effective for only one week. Cups that were hidden had a very low larval mortality
compared with exposed cups. Bti misting targeted directly into cups at a distance of 1 m was
effective for up to four weeks in cups placed in the shade and partial shade.
Keywords: Bacillus thuringensis israelensis; Residual effect; Aedes albopictus; Singapore.
Introduction
Mosquito-borne infectious diseases have become a major public health threat worldwide
today. The Asian tiger mosquito, Aedes albopictus, can transmit pathogenic organisms
including chikungunya,[1] dengue[2-4] West Nile, Japanese encephalitis and yellow fever viruses.
Originally native to south-east Asia, Ae. albopictus has now spread across the world.[5].
#
181
Bti misting to control Aedes albopictus in Singapore
Ae. albopictus is considered a rural mosquito[6] as it prefers to breed in areas with
vegetation, rests outdoors, and can be difficult to control. Strategies aimed at reduction
of oviposition sites have shown to be effective but are labour-intensive and, thus, may
not be the best approach to control Ae. albopictus. In Singapore, different methods have
been evaluated to control this vector. Chemical insecticides have been used for many
decades, of which Temephos has been the larvicide of choice for many years. However,
development of resistance to different adulticides and larvicides has been observed in the
last two decades.[7,8]
Increasing mosquito resistance has led to the search for alternative strategies for mosquito
control, such as the use of the biological control agent, Bacillus thuringiensis israelensis (Bti).
This entomopathogen kills mosquito larvae by producing toxic crystalline proteins. Since
the discovery of Bti in 1976, extensive studies on the application and residual activity of
different formulations of Bti have been carried out in many countries for mosquito control.
Published results show that Vectobac tablet formulation provides an average of more than
80% mortality to Aedes ageypti for between 2 to 5 months.[9-11] However, direct application
of Vectobac WDG in containers provided between 95% to 70% mortality to Ae. aegypti
and residual efficacy ranged between 1–3 months depending on temperature and rainfall.
[12-14]
, while after four weeks of misting Bti (Vectobac WG) in a housing area in Malaysia, the
ovitrap index decreased by at least 50%.[15] On the whole, Vectobac 12 AS on various Culex
spp only provided about 80% mortality for about one week.[16,17] However, the application
of Bti to each and every breeding site is labour-intensive and thus various other application
techniques have been studied to overcome this constraint .[15,18-20]
In 2008, Singapore experienced the first outbreak of chikungunya virus (CHIKV). The
major outbreaks were largely seen in semi-urban and rural parts of Singapore, which included
some of the major industrial areas. Ae. albopictus was identified as the main vector for the
virus transmission.[6] Therefore, this study was conducted in a CHIKV-affected industrial
area in Singapore to determine the residual efficacy of Bti misting against Ae. albopictus
mosquitoes.
Study area
The study was carried out in Kranji Loop in Sungai Kadut, Singapore, from April to August
2009. This is an industrial area located in the north-west part of the country (1° 17’ 52’’N,
103° 51’ 05”E). Three sites were selected; two were assigned to the Bti treatment and one
served as control. Two of the selected sites were woodwork factories (one served as control),
manufacturing timber products while the third site was a scrapyard of reconditioned vehicles
and tyres. Each study area was approximately 0.37 hectares in size. In these factories many
182
goods were placed haphazardly and thus it was difficult to find and destroy each and
every breeding site. The locations were selected based on earlier records of chikungunya
transmission[6] and high Aedes spp. populations. The owners’ consent was obtained before
the start of the study.
An autocidal ovitrap was used as a surveillance tool to monitor the Aedes spp. populations.
This ovitrap consists of two paddles and does not become a breeding site.[21] Twenty ovitraps,
with hay infusion water, were placed at each site for six weeks from April to May 2009
(pre-treatment) and from July to August (post-treatment). Ovitraps were placed outdoors at
randomly selected sites. Each week, the wooden paddles were replaced with new paddles.
If present, larvae were identified and counted. The hay infusion water was renewed weekly.
The paddles were brought back to the laboratory where the eggs were counted and allowed
to hatch and the larvae that emerged were identified.
Bti formulations and treatment
Bti was obtained as a water-dispersible granule formulation VectoBac WG (AM65-52) (Valent
Biosciences Cooperation, USA). This formulation is 3000 ITU/mg. Pre-testing was carried
out using the same spray personnel and misting device to determine the volume of water
needed to provide complete coverage to the study area. VectoBac WG was applied at the
rate of 500 g/hectare to the treatment sites according to the manufacturer’s recommendation
and the same volume (60 litres) of water was sprayed at the control site. Spraying was carried
out on two occasions (between 06.00 and 09.00 hours), using Backpack mistblower, Stihl
420 SR.[16]. Two spray personnel covered each area and the mist was targeted at all potential
breeding sites. Nozzle size dial no. 2 (average discharge rate of about 500 ml per minute)
was used in open areas and size 4 was used in covered drains.
Residual effect of Bti over time
The effectiveness of Bti misting was evaluated by determining larval mortality. Just before
misting, wet (n=40) and dry cups (n=40) (all the cups were plastic and transparent with
a transparent lid) were placed randomly with the lids open. Forty wet and dry cups were
exposed to Bti misting on two occasions and an additional 40 plastic cups for one occasion.
Each wet cup contained 500 ml seasoned water (water stored overnight at room temperature
(26 °C).
In order to study residual activity of Bti, 20 laboratory-bred Ae. albopictus mosquito
larvae (L3) were placed in each cup one hour after misting. Mortality was recorded 24
hours later. A fresh batch of larvae was introduced into the cups on a weekly basis and the
183
mortality was recorded. Dry cups were filled with 500 ml of water before introducing larvae.
The cups were closed with transparent plastic lids to avoid egg-laying by wild mosquitoes.
All larvae introduced were discarded before starting a new test. This routine was conducted
at weekly intervals for three weeks.
Residual effect of Bti at various distances and in different environmental conditions
Since we also wanted to estimate the residual activity and distance coverage of the misting
treatment, a small experiment was performed to monitor these effects. Dry plastic cups
(500 ml capacity) were placed at horizontal distances of 1, 5, 10, 15 and 20 m from the
spray machine. Misting was carried out using the Stihl 420 SR mistblower and the same
concentration of Bti was used as mentioned in the previous trial. For each distance, there
were three replicate cups. These cups were filled with water at weekly intervals for four
weeks. This was done to simulate what would happen if dry containers were treated and
later filled with water when it rains.
One set of cups was treated and then placed in a shaded area (under a hut) and another
set was placed in a semi-shaded area (under a tree) for the duration of the four-week period.
Twenty laboratory-bred Ae. albopictus larvae (L3) were introduced into each cup and the
mortality was recorded after 24 hours. The cups were closed to avoid egg-laying by wild
mosquitoes. All larvae from previous introductions were discarded before starting a new
test.
The data were log-transformed to stabilize the variance. The Kruskal-Wallis exact test was
used to detect the differences in egg counts and residual effects of Bti treatment, with factors
for treatment sites and time. P<0.05 was considered as significant. All analyses were carried
out using Minitab 8.5 and SPSS-11.
Results
The mean egg density index (EDI) varied between 7.4±2.86 (Site 2) and 49.9±10.7 eggs/
ovitrap (control site) during the pre-test period. The mean EDI across all areas was 28.4±1.8
eggs/ovitrap. There was no significant difference in EDI among the three sites (p>0.05).
Figure 1 shows the EDI during pre- and post-treatment sampling.
184
Figure 1: Trend of Ae. albopictus eggs/ovitrap before and after treating with Bti WG as
measured with ovitrap surveillance conducted on alternate weeks with pre- (week 1-6)
and post-treatments (week 13-18). Bti application was done in 9th and 11th week
60
Site 1 (T)
Site 2 (T)
Site (C)
Eggs/per ovitrap
50
40
30
Bti application
20
10
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Weeks
Two VectoBac WG (Bti) treatments were applied three weeks after pre-treatment
surveillance with an interval of one week between two misting treatments. The Mean EDI
was reduced in all sites including the untreated control site post-treatment. Mean EDI for
all areas together=21.4±1.1. Interestingly, the reduction of egg density followed the same
pattern for all three sites. EDI was not significantly different among the three sites after Bti
application (p>0.05) (Figure 1).
Residual effect of Bti over time
Both wet and dry cups showed residual activity only up to one week after one or two misting
treatments. Dry cups had a higher mortality than the wet cups but the differences in values
were not significant (p>0.05). The mortality in the wet and dry cups after one or two Bti
treatments was less than 80% (Figure 2) for the first week. This could be due to the fact that
some cups were hidden and could not be reached by the misting treatment. There was a
highly significant difference in the mortality of larvae between the hidden and exposed cups
(p<0.001). Figure 3 shows the mortality of the exposed and hidden cups.
Residual effect of Bti at various distances and in different environmental conditions
When Bti was applied directly to the cups at various distances, cups at 1 m distance retained
insecticidal activity for up to four weeks in cups placed in the shade and partial shade. Larvae
in cups in complete shade experienced a significantly higher mortality (p<0.05) than those
in partial shade.
185
Figure 2: Mortality of Ae. albopictus larvae exposed to Bti-treated wet and dry containers.
(a) Mortality after one Bti misting. (b) Mortality after two Bti misting
(a)
% Mortality
100
Wet
80
Dry
60
40
20
0
Site 1
Site 2
Cotrol
Site 1
Site 2
1
Cotrol
Site 1
2
Site 2
Cotrol
3
Week
(b)
% Mortality
100
80
Wet
60
Dry
40
20
0
Site 1
Site 2
1
Cotrol
Site 1
Site 2
2
Cotrol
Site 1
Site 2
Cotrol
3
Week
186
Figure 3: Mortality of larvae in cups that were exposed as well as hidden. Exposed cups
had higher mortality as spraymen were able to spray directly into the cups. Misting
obviously could not reach the cups that were hidden
When water was introduced at various intervals, the residual effect was observed for up
to four weeks in cups at 1 m distance. Cups in the shade and partial shade showed more
than 60% mortality when tested at four weeks after Bti application (Figure 4).
Discussion
In this study, a similar reduction in EDI values was observed at all sites (control site inclusive)
after misting. Since ovitrap surveillance removed the majority of the eggs in all three sites
on a weekly basis, the mosquito life-cycle was disrupted. Thus, the observed effect may be
attributed to natural fluctuations in the mosquito population in the absence of any Bti-related
effects. Similar observations were reported by Lee et al.[15] Their first treatment of Bti using
a Backpack mistblower also failed to decrease Ae. albopictus populations and a decline
occurred only after a second treatment.
187
Figure 4: Mortality of Ae. albopictus larvae exposed to Bti-treated containers
placed in the shade and partial shade. (a) Four consecutive weeks.
(b) Three consecutive weeks. (c) Two consecutive weeks. (d) For one week.
(a)
100.00%
Shade
80.00%
P. Shade
60.00%
40.00%
15m
20m
20m
3
10m
5m
1m
20m
15m
10m
5m
1m
20m
2
15m
1
15m
10m
5m
1m
20m
15m
10m
5m
0.00%
1m
20.00%
4
Weeks
(b)
100%
80%
Shade
P. Shade
60%
40%
1
2
3
10m
5m
1m
20m
15m
10m
5m
1m
20m
15m
10m
5m
1m
20m
15m
5m
1m
0%
10m
20%
4
Weeks
188
(c)
100%
80%
Shade
60%
P. Shade
40%
15m
20m
20m
3
10m
5m
1m
20m
15m
10m
5m
1m
20m
15m
2
15m
1
10m
5m
1m
20m
15m
5m
1m
0%
10m
20%
4
Weeks
(d)
100%
80%
60%
Shade
P. Shade
40%
20%
1
2
Weeks
3
10m
5m
1m
20m
15m
10m
5m
1m
20m
15m
10m
5m
1m
20m
15m
10m
5m
1m
0%
4
189
In this study, the residual efficacy of Bti misting using wet and dry cups was effective
for only one week. If the residual activity can be prolonged, perhaps Bti treatment could
serve as a useful control tool. Repeated treatment over a short period of time has shown to
increase the duration of persistence, but it failed to increase with higher concentrations of
the product.[22] Experiments have shown that Bacillus sphaericus (combined with spore-crystal
powders of the Cyt1A strain) provides greater residual activity than Bti because of the longer
persistence of the spores in the environment and their recycling potential in the gut of the
larvae after dying, leading to control of several mosquito generations.[23]
This type of misting application was not an effective method of dispersing this larvicide
as it did not reach hidden containers (Figure 3). However, misting may be useful in open
areas. A study by Aldemir[17] in drainage canals and flooded plains in Turkey has shown 83%
mortality for Aedes species up to 12 days post application. Experiments done in open fields
in Kenya have shown low doses (200 g/ha) to be effective in suppressing the late instars and
resulting pupae of Anopheles species.[22] In forested habitats, Bti collected in leaf litter have
toxins and spores protected and may also have long-term effect.[24] Similarly, it has been
shown that in a forested area it is possible to control Ae.albopictus by misting Bti.[25]
Direct application of Bti formulation into earthen and glass jars, rather than misting,
has provided larvicidal activity (49 days and 25 days respectively) with good residual effects
under laboratory and field conditions.[14] Many other studies have shown dry cups to be
effective up to 7–14 days using different application methods.[12,19] Combination of Bti with
chemical pesticides has proven to be a promising Aedes control method without having any
antagonistic effect.[26]
It is known that many environmental factors affect the control activity of Bti. In this
study when misting was carried out directly to the cups, the residual efficacy was 1–3 weeks
depending on environmental conditions. Cups placed in the shade were protected from
direct sunlight and have shown a higher mortality than the cups placed in partial shade
(Figure 5). Melo-Santos[9] have shown a similar trend, recording a decline in the residual
activity of Bti, 13–35 days when exposed to sunlight. Other factors also play a significant role
in the residual activity of Bti. Boisvert[27] has demonstrated that younger instar larvae tend to
be more susceptible than older ones for most mosquito species, as late instars lack ingestion
due to less feeding before pupation. Low-density larval populations have also shown higher
mortalities than high-density populations. The presence of organic and inorganic particles
has shown to reduce the larval mortality as fewer toxin particles were ingested per unit time
and higher rates of application were recommended to control mosquito larvae.[27,28] There
have been reports of reduced survival rates at the offspring stage, reduced fecundity and a
prolonged developmental period for the Aedes larvae after Bti exposure.[29]
In a recent study in Australia,[30] the application of very high doses (10× normal dose) of
Bti directly to wet or dry containers provided 100% mortality of Ae. aegypti for over seven
weeks. Although Bti is recognized as an efficient bioinsecticide, suitable formulations that
provide residual efficacy under field conditions are required.
190
Direct application to containers may be time-consuming and one may argue that
search-and-destroy practices may be a better choice. In this industrial set-up in Singapore it
would be difficult to find every breeding site. Even if weekly misting of Bti is carried out, it
will be impossible to keep that area free of Ae. albopictus, as misting may not reach every
breeding site. At the same time, considerable amounts of money will be spent on the misting
operations. Thus, the cost-effectiveness of such measures has to be evaluated before misting
can be introduced. Although misting appears to be a good strategy for controlling mosquito
larvae in general,[31] its efficacy on container-breeders like Ae. albopictus remains doubtful.
This study has shown that in an industrial area, misting treatments were unable to reach all
potential breeding sites.
Acknowledgments
We thank the staff of South West Regional Office, Singapore, for their technical assistance
and providing testing sites, especially Tsui Ka Lok, Abdul Manap Bin Mustajab, Johari Bin
Sarlan, Dre Hassan Bin Mohamad, Rahmat Bin Arwee, Abdullah Amat, A. Aziz M. Ali and
M. Arip Osman, for their support during the fogging operations.
Continued support from colleagues from the Environmental Health Institute, especially
Muhd Aliff, Lim Jixiang, Leon Leong, Lee Kim Sung, Irene Li, Jeslyn Wong and Sharon Tan,
who gave great support in the field investigations, is highly appreciated. We are also grateful
to Ms Seleena Benjamin of Valence Bio Science for her support in conducting a preliminary
study trial. This work was fully funded by National Environmental Agency, Singapore.
References
[1] Delatte H, Paupy C, Dehecq JS, Thiria J, Failloux AB, Fontenille D. Aedes albopictus, vector of
chikungunya and dengue viruses in Reunion Island: biology and control. Parasite. 2008; 15: 3-13.
[2] Ibanez-Bernal S, Briseno B, Mutebi JP, Argot E, Rodriguez G, Martinez-Campos C, Paz R, de la Fuente-San
Roman P, Tapia-Conyer R, Flisser A: First record in America of Aedes albopictus naturally infected with
dengue virus during the 1995 outbreak at Reynosa, Mexico. Med Vet Entomol. 1997; 11: 305-309.
[3] Rudnick A, Chan YC: Dengue type 2 Virus in naturally infected Aedes albopictus mosquitoes in
Singapore. Science. 1965; 149: 638-639.
[4] Serufo JC, de Oca HM, Tavares VA, Souza AM, Rosa RV, Jamal MC, Lemos JR, Oliveira MA, Nogueira
RM, Schatzmayr HG. Isolation of dengue virus type 1 from larvae of Aedes albopictus in Campos Altos
city, State of Minas Gerais, Brazil. Mem Inst Oswaldo Cruz. 1993; 88: 503-504.
[5] Gratz NG. Critical review of the vector status of Aedes albopictus. Med Vet Entomol. 2004; 18: 215227.
[6] Ng LC, Tan LK, Tan CH, Tan SS, Hapuarachchi HC, Pok KY, Lai YL, Lam-Phua SG, Bucht G, Lin RT, Leo
YS, Tan BH, Han HK, Ooi PL, James L, Khoo SP. Entomologic and virologic investigation of Chikungunya,
Singapore. Emerg Infect Dis. 2009; 15: 1243-1249.
191
[7] Liew C L-PS, Curtis CF. The susceptibility status of Singapore Aedes vectors to temephos and Pirimiphosmethyl. In Proc Inter Cong Parasitol Trop Med. Kuala Lumpur: Malaysian Society of Parasitology and
Tropical Medicine, 1994. p. 68-77.
[8] Ping LT, Yatiman R, Gek LP. S Susceptibility of adult field strains of Aedes aegypti and Aedes albopictus
in Singapore to pirimiphos-methyl and permethrin. J Am Mosq Control Assoc. 2001; 17:144-146.
[9] Melo-Santos MAV, Sanches EG, Jesus FJ, Regis L: Evaluation of a new tablet formulation based on
Bacillus thuringiensis sorovar. israelensis for larvicidal control of Aedes aegypti. Memórias do Instituto
Oswaldo Cruz. 2001; 96: 859-860.
[10] Benjamin S, Rath A, Fook CY, Lim LH. Efficacy of a Bacillus thuringiensis israelensis tablet formulation,
vectobac DT, for control of dengue mosquito vectors in potable water containers. Southeast Asian J
Trop Med Public Health. 2005; 36: 879-892.
[11] Armengol G, Hernandez J, Velez JG, Orduz S. Long-lasting effects of a Bacillus thuringiensis serovar
israelensis experimental tablet formulation for Aedes aegypti (Diptera: Culicidae) control. J Econ
Entomol. 2006; 99:1590-1595.
[12] Lima JBP, Melo NV, Valle D. Persistence of Vectobac WDG and Metoprag S-2G against Aedes aegypti
larvae using a semi-field bioassay in Rio de Janeiro, Brazil. Revista do Instituto de Medicina Tropical
de São Paulo. 2005; 47: 7-12.
[13] Lima JBP, Melo NV, Valle D. Residual effect of two Bacillus thuringiensis var. israelensis products assayed
against Aedes aegypti (Diptera: Culicidae) in laboratory and outdoors at Rio de Janeiro, Brazil. Revista
do Instituto de Medicina Tropical de São Paulo. 2005; 47:125-130.
[14] Lee YW, Zairi J. Field evaluation of Bacillus thuringiensis H-14 against Aedes mosquitoes. Trop Biomed.
2006; 23: 37-44.
[15] Lee HL, Chen CD, Masri SM, Chiang YF, Chooi KH, Benjamin S. Impact of larviciding with a Bacillus
thuringiensis israelensis formulation, VectoBac WG, on dengue mosquito vectors in a dengue endemic
site in Selangor State, Malaysia. Southeast Asian J Trop Med Public Health. 2008; 39: 601-609.
[16] Russell TL, Brown MD, Purdie DM, Ryan PA, Kay BH. Efficacy of VectoBac (Bacillus thuringiensis
variety israelensis) formulations for mosquito control in Australia. Journal of Economic Entomology.
2003; 96:1786-1791.
[17] Aldemir A. Initial and Residual Activity of VectoBac® 12 AS, VectoBac® WDG, and VectoLex® WDG
for Control of Mosquitoes in Ararat Valley, Turkey. Journal of the American Mosquito Control Association.
2009; 25:113-116.
[18] Knepper RG, Wagner SA, Walker ED. Aerially applied, liquid Bacillus thuringiensis var. israelensis
(H-14) for control of spring Aedes mosquitoes in Michigan. Journal of the American Mosquito Control
Association. 1991; 7: 307-309.
[19] Seleena P, Lee H, Chiang Y. Thermal application of Bacillus thuringiensis serovar israelensis for dengue
vector control. Journal of Vector Ecology. 2001; 26:110-113.
[20] Seleena P, Lee HL, Chooi KH, Junaidih S. Space spraying of bacterial and chemical insecticides against
Anopheles balabacensis Baisas for the control of malaria in Sabah, East Malaysia. Southeast Asian J Trop
Med Public Health. 2004; 35: 68-78.
[21] Lok CK, Kiat NS, Koh TK. An autocidal ovitrap for the control and possible eradication of Aedes aegypti.
Southeast Asian J Trop Med Public Health. 1977 Mar; 8(1): 56-62.
192
[22] Fillinger U, Knols BG, Becker N. Efficacy and efficiency of new Bacillus thuringiensis var israelensis
and Bacillus sphaericus formulations against Afrotropical anophelines in Western Kenya. Trop Med Int
Health. 2003; 8: 37-47.
[23] Wirth MC, Federici BA, Walton WE. Cyt1A from Bacillus thuringiensis synergizes activity of Bacillus
sphaericus against Aedes aegypti (Diptera: Culicidae). Appl Environ Microbiol. 2000; 66:1093-7.
[24] Tilquin M, Paris M, Reynaud S, Despres L, Ravanel P, Geremia RA, Gury J. Long lasting persistence of
Bacillus thuringiensis Subsp. israelensis (Bti) in mosquito natural habitats. PLoS One. 2008; 3: e3432.
[25] Lam PH, Boon CS, Yng NY, Benjamin S. Aedes albopictus control with spray application of Bacillus
thuringieensis israelensis strain AM 65-52. Southeast Asian J Trop Med Public Health. 2010 Sep;
41(5):1071-81.
[26] Seleena P, Lee HL, Chiang YF. Compatibility of Bacillus thuringiensis serovar israelensis and chemical
insecticides for the control of Aedes mosquitoes. J Vector Ecol. 1999; 24: 216-223.
[27] Boisvert MP. Utilization of Bacillus thuringiensis var. israelensis (Bti)-based formulations for the biological
control of mosquitoes in Canada. Société de Protection des Forêts contre les Insectes et Maladies.
2005: 87-93.
[28] Stoops CA. Influence of Bacillus thuringiensis var. israelensis on oviposition of Aedes albopictus (Skuse).
Journal of Vector Ecology. 2005; 30: 41-4.
[29] Wang L, Jaal Z. Sublethal effects of Bacillus thuringiensis H-14 on the survival rate, longevity, fecundity
and F1 generation developmental period of Aedes aegypti. Dengue Bulletin. 2005; 29:192-6.
[30] Ritchie SA, Rapley LP, Benjamin S. Bacillus thuringiensis var. israelensis (Bti) provides residual control
of Aedes aegypti in small containers. Am J Trop Med Hyg. 2010; 82(6):1053-9.
[31] Lee VJ, Ow S, Heah H, Tan MY, Lam P, Ng LC, Lam-Phua SG, Imran AQ, Seet B. Elimination of malaria
risk through integrated combination strategies in a tropical military training island. Am J Trop Med Hyg.
2010; 82(6): 1024-9.
193
Susceptibility of Aedes aegypti to insecticides in
Ranchi city, Jharkhand state, India
M.K. Das,a R.K. Singh,b R.K. Lalc & R.C. Dhimanb#
National Institute of Malaria Research (Indian Council of Medical Research), Field Unit,
Ranchi 835301, India.
a
National Institute of Malaria Research (Indian Council of Medical Research), Sector-8, Dwarka,
New Delhi 110077, India.
b
Zonal Malaria Office, South Chhotanagpur Division, Ranchi 834002, India.
c
Abstract
A study was undertaken to find out the susceptibility status of the dengue vector, Aedes aegypti, to
various insecticides in 2008 in Ranchi, capital of Jharkhand state, India, using the WHO standard
susceptibility test kits. The susceptibility test showed that Ae. aegypti mosquitoes were resistant
to DDT but susceptible to malathion, deltamethrin and cyfluthrin. The mortalities of adults, using
diagnostic dosages of DDT (4.0%) were 19.5%; malathion (5.0%) 88.83%; deltamethrin (0.05%)
99.57%; and cyfluthrin (0.15%) 93.33%. For the larval susceptibility test on III and IV instar,
Ae. aegypti larvae collected from the field were tested according to the WHO-recommended
diagnostic dosages for Aedes spp against temephos (0.02 mg/L). The tests revealed that larvae of
Aedes aegypti species were susceptible to temephos and the mortality was 96.53% to 100% within
24 hours of treatment.
Keywords: Aedes aegypti; Insecticide susceptibility; Ranchi city; Jharkhand. Introduction
The Indian state of Jharkhand is home to ethnic tribal populations and is hyperendemic for
malaria.[1] Since 1958, the state has been receiving two rounds of DDT and other insecticides
spraying @ 100 mg/sq mt[2-3] for vector control. India is also endemic for dengue fever (DF)/
dengue haemorrhagic fever (DHF). The first outbreak of DF/DHF was reported in Calcutta
(now Kolkata) in 1963[4] and it soon spread to all towns in the country. The disease has now
reached most of the rural areas,[5] with the spread of Ae. aegypti facilitated by introduction of
safe drinking water supply. The disease has become hyperendemic as all the four serotypes
of DENV are now circulating in the country.
#
194
Susceptibility of Aedes aegypti to insecticides in Ranchi city
In 2006, Ranchi, the capital of Jharkhand state, reported its first-ever epidemic of DF, with
194 clinically-suspected and 13 serologically-confirmed cases. During 2010, 11 serologicallyconfirmed DF cases were reported from the city.[6-7] To counter this, the state government
and local health authorities initiated dengue control activities. As per the guidelines of the
National Vector-Borne Diseases Control Programme (NVBDCP), the interventions comprised
of (i) source reduction; (ii) larviciding with temephos; and (iii) supportive interventions like
behaviour change communication (BCC). To assist local health authorities, the Ranchi field
unit of the National Institute of Malaria Research carried out studies on the susceptibility of
adult and immature stages of Ae. aegypti to insecticides used under the NVBDCP.
Methods and materials
The susceptibility of Ae. aegypti adults and larvae to insecticides and larvicides was studied
during 2008 by using the WHO standard diagnostic dosages and test kits of various
insecticides, namely, organochlorine (DDT), organophosphorous (malathion) and synthetic
pyrethroids (deltamethrin and cyfluthrin) for adult mosquitoes, and to temephos (larvicide)
under the field lab conditions. The WHO standard procedures were adopted for adult and
larval bioassays.[8-9]
Wild Ae. aegypti mosquitoes were collected from human dwellings in the morning hours
(0600 to 1000 hrs) with the help of suction tube and flash light and identified up to species
level with the help of standard identification keys.[10] The collected adult female mosquitoes
were allowed to feed on 10% glucose solution-soaked cotton pads and transported in caged
cloth to the field laboratory maintained at room temperature of 27±2 °C and relative
humidity of 75%–85%. Insecticide-treated papers received from Universitat Sans of Malaysia,
with different diagnostic dosages, were used for the detection of resistance to DDT (4.0%),
malathion (5.0%), deltamethrin (0.05%) and cyfluthrin (0.15%), respectively.
Susceptibility test for adult mosquitoes
Mosquitoes were exposed against the diagnostic dosages of insecticides for one hour. Three
replicates, usually containing 15–25 female mosquitoes, were taken simultaneously for
each insecticide. Control replicate was also held parallel to each test. After exposure for
the requisite period, the holding tubes were kept for recovery in dark and cool chambers
maintained at the same room temperature and relative humidity. Cotton pads soaked in
10% glucose solution were provided as supplementary food during the recovery period of
24 hours. The mortalities were calculated by scoring the dead and alive mosquitoes and
corrected by Abbott’s formula.[11]
195
Susceptibility test for mosquito larvae
For larval susceptibility tests, III and IV instar larvae of Ae. aegypti were collected from the
known Ae. aegypti breeding containers, separated and washed in tap water to remove debris
and kept under observation for 24 hours to detect and remove unhealthy or dead larvae.
The larvae were tested against the WHO-recommended diagnostic dosages of temephos
(0.02 mg/L). Three replicates and one control, each containing 20 to 25 larvae, were taken
for each insecticide. The rest of the larvae were kept for pupation and hatching. All emerging
adults were identified as Ae. aegypti. The mortalities were calculated by scoring the dead,
moribund and alive larvae after 24 hours of recovery period. Both dead and moribund
larvae were treated as dead.
Results
The results of the susceptibility of Ae. aegypti adult mosquitoes to different diagnostic doses of
insecticides are given in Table 1. The corrected percent mortality of adult Ae. aegypti to DDT
(4.0%) was 19.5%, to malathion (5.0%) was 88.83%, to deltamethrin (0.05%) was 90.57%
and to cyfluthrin (0.15%) was 93.32%. Thus, Ae. aegypti mosquitoes tested in this area were
found resistant to DDT but were susceptible to malathion, deltamethrin and cyfluthrin.
Table 1: Susceptibility of Aedes aegypti to various insecticides in Ranchi city,
Jharkhand state, India, during 2008
Insecticide doses used
No. of mosquitoes
exposed
No. of dead
mosquitoes
Corrected (%) mortality
in adult mosquitoes
Control
Test
Control
Test
Control
Test
DDT (4.0%)
100
300
6
73
6.00
19.5
Malathion (5.0%)
75
265
4
237
5.33
88.83
Deltamethrin (0.05%)
75
250
5
228
6.66
90.57
Cyfluthrin (0.15%)
100
300
5
281
5.00
93.32
The results of the larval susceptibility tests revealed that larvae of Ae. aegypti were
susceptible to temephos (0.02 mg/L) with 96.53% to 100% mortality within 24 hours
of treatment (Table 2).
196
Table 2: Susceptibility status of larvae of Aedes aegypti to temephos (50%EC) (@02mg/L)
in Ranchi city, Jharkhand state, India, during 2008
Larvae exposed in
control
Larvae exposed in
test
Corrected (%) mortality
Pandra
25
75
100.00
Durenda
20
60
97.33
Karwala
25
75
100.00
Kadru
20
20
98.67
HEC Colony
25
75
96.53
Localities
Discussion
Madhukar and Pillai reported resistance in the Indian strains of Ae. aegypti mosquitoes to
insecticides.[12] Azeez reported resistance in Ae. aegypti mosquitoes to DDT from Jharia,
Dhanbad district, and, recently, from Koderma district, both in Jharkhand state[3,13] (erstwhile
Bihar state), but there has been no report of resistance in dengue vectors to other insecticides
in Ranchi city.
The resistance to DDT may be due to the prolonged exposure through indoor residual
spray (IRS) of the insecticide since 1958. The strategy for control of Ae. aegypti in India is
based on the use of temephos (50%EC) as chemical larvicide, bacticide and sphericide as
bio-larvicides and larvivorous fish. During epidemics, thermal fogging is also resorted to.
Though indoor residual spray of DDT is not recommended for use against Aedes
mosquitoes, it has been used for the control of Ae. aegypti during outbreaks in the Americas,
United Kingdom, Australia and Thailand.[14-17] Local health authorities in Queensland,
Australia,[14] in addition to normal methods of control (source reduction and larvicidal activities
for larval control), also sprayed pyrethroids under the beds, tables and other items of furniture
against Ae. aegypti. In India also, Ae. aegypti population under the influence of excito
repellency of DDT spray, rest on unsprayable surfaces. In order to control epidemics, a similar
procedure, i.e. spraying with an appropriate insecticides, to which Ae. aegypti mosquitoes
are susceptible, can be undertaken for the quick control of dengue epidemics.
Acknowledgements
The authors are most grateful to Mr N.L. Kalra for his valuable suggestions. The laboratory
and field assistance given by the staff of NIMR, field unit, Ranchi, is gratefully acknowledged.
The authors are also thankful to the staff of the District Malaria Officer, Ranchi, for providing
information on the dengue incidence and use of insecticides in IRS activities.
197
References
[1] Anon. Malaria and its control in India. Vol. I. New Delhi: Directorate of National Malaria Eradication
Programme, India, 1986. 254.
[2] Singh RK, Dhiman RC, Mittal PK, Das MK. Susceptibly of malaria vectors to insecticides in Gumla
district, Jharkhand state, India. Jour Vect Bor Dis. 2010; 47(2): 116-118.
[3] Singh RK, Dhiman RC, Mittal PK, Dua VK. Susceptibly status of dengue vectors against various insecticides
in Koderma (Jharkhand), India. Jour Vect Bor Dis. 2011; 48(2): 116-118.
[4] Ramakrisnan SP, Gelfand HM, PN Bose, PN Sehgal, RN Mukerjee.The Epidemic of Acute Hemorrhagic
fever in Calcutta, in 1963. Epidemiological inquiry. Ind Jour Med Res. 1964, 52; 633-650.
[5] Kumar A, Sharma SK, Padbidri VS, Thakare JP, Jain DC, Datta KK. An outbreak of Dengue fever in rural
areas of Northern India. J Com Dis. 2001; 33(4): 274-281.
[6] Directorate General of Health Services. National Vector Borne Disease Control Programme. Delhi:
Ministry of Health and Family Welfare, 2010. http://nvbdcp.gov.in/ - accessed 13 January 2012.
[7] Singh RK, Das MK, Dhiman RC, Mittal PK, Sinha ATS. Preliminary investigation of dengue vectors in
Ranchi, India. Jour Vec Bor Dis. 2007, 45(2):171-173.
[8] Instructions for determining the susceptibility or resistance of adult mosquito to organo-chlorine
organophosphate and carbonate insecticides – Diagnostic test 1981. WHO/VBC/81-806.
[9] Instructions for determining the susceptibility or resistance of mosquito larvae to insecticides 1981.
WHO/VBC/81-807.
[10] Das BP, Kaul SM. Pictorial key to the common Indian species of Aedes (Stegomyia) mosquitoes. J Com
Dis. 1998; 30: 123-127.
[11] Abbott WS. A method of computing the effectiveness of an insecticide. J Econ Entomol. 1925, 18;
265-267.
[12] Madhukar BVR, Pillai MMK. Insecticide susceptibility in Indian strains of Aedes aegypti (Linn). Mosq
News. 1968; 28: 222-225.
[13] Azeez SA. A Note on the prevalence and susceptibility status of Aedes (Stegomyia) aegypti (Linn) in
Jharia, Dhanbad district (Bihar). Bull Ind Soc Mal Com Dis. 1967; 4: 59-62
[14] Ritchie SA, Hanna JN, Hills SL, Piipanen JP, Mcbride WJH, Pyke A, Spark RL. Dengue control in
Queensland and selective indoor residual spraying. Dengue Bull. 2002; 26: 7-13.
[15] Anon. Dengue haemorrhagic fever: diagnosis, treatment, prevention and control. II edn. Geneva: World
Health Organization, 1997. pp. 1-84.
[16] Charles EK. Filariasis control by DDT residual house spraying, Saint CROX, Virgin Island. Public Health
Report. 1949; 64; 27.
[17] Pimsamarn S, Sornpeng W, Aksip S, Paeporn P, Limpawitthayakul M. Detection of insecticide resistance
in Aedes aegypti to organophosphate and synthetic pyrethroid compounds in the north-east of Thailand.
Dengue Bull. 2009; 33: 194-202.
198
Dengue awareness survey among women participants
from periurban areas of Chennai, India
R. Ramanibai# & Kanniga S.
Unit of Biomonitoring, Department of Zoology, University of Madras,
Guindy Campus, Chennai – 25, India.
Abstract
Dengue is one of the mosquito-borne diseases spread by Aedes aegypti and Aedes albopictus.
Dengue fever has been reported regularly in Tamil Nadu, especially in Chennai. In the year 2001,
737 cases were reported from Chennai out of a total of 816 cases for the whole state. In the
absence of a vaccine for dengue, control of vector population is the best option. This could be
effective only if there is community participation. In order to assess the knowledge of housewives
in periurban areas of south Chennai, a knowledge, attitude and practice (KAP) survey was carried
out in 2009. The study showed that 77.9% of the study population was unaware of dengue and
were not aware of the behaviour of its vector like breeding sites, biting time, etc. To prevent
mosquito bites, 45.6% of the respondents used coils, but none of the interviewees adopted any
preventive measures against this day-biting mosquito. This survey revealed that the knowledge
regarding dengue was too poor among the people.
Keywords: Dengue; Aedes aegypti; Questionnaire method; Awareness; Periurban; Chennai; India.
Introduction
Dengue fever (DF)/dengue haemorrhagic fever (DHF), transmitted by Aedes aegypti, is an
arboviral disease endemic in the Asian subcontinent.[1]
In India, the first outbreak of DHF occurred in Kolkata in 1963[2] and in Delhi in 1988.[3]
Dengue fever cases had been reported frequently in Tamil Nadu state, especially in Chennai.
During 2001, the state reported a total of 816 DF cases, of which Chennai city alone
contributed 737 cases (90.3%).[4] The peak of these cases were recorded during September
to December (north-eastern monsoon season).
#
199
Dengue awareness survey among women participants from periurban areas of Chennai, India
The rapid increase in human population, lack of awareness among people, environmental
changes, social changes and increased breeding of vector mosquitoes resulted in increased
dengue transmission.[5,6] All four serotypes, DENV-1, DENV-2, DENV-3 and DENV-4, have
been reported in Chennai.
The Aedes aegypti mosquito is responsible for the spread of dengue fever breeds in
man-made receptacles and around urban environments such as households, construction
sites, office complexes, schools, hospitals and factories. Water storage drums, cisterns, flower
vases, cement tanks, plastic and metal drums, tyres, bottles, tin cans, coconut shells and
other such discarded containers which can hold rainwater, overhead tanks, ground water
storage tank, etc., are the primary habitats.[7,8]
In Chennai, particularly in the periurban regions, the water supply is irregular, inhabitants
tend to store water for household use in several containers, and this in turn increases the
number of larval habitats.
Since there is no vaccine, vector control is the ideal way to control dengue. Vector control
methods can be successful only if there is community participation, and, for the success of a
community-based programme, it is important to asses the community’s perception regarding
the disease, its mode of transmission and breeding sites. Hence, this study was conducted
in 2009 to asses the knowledge, attitude and practice (KAP) regarding dengue fever among
women in a periurban region of south Chennai.
Chennai is located at 13° 04N and 80° 17E on the south-east coast of India and in the northeast corner of Tamil Nadu state. The lowest temperature recorded here is 15.8 °C and the
highest 44 °C. The relative humidity ranges between 61%–80%. The average annual rainfall
is about 1300 mm. The city gets most of its rainfall from the north-eastern monsoon during
September to mid-November.[4]
A total of 31 periurban areas of south Chennai were subjected to questionnaire method.
The study was conducted by the interview technique. The study population consisted of
only housewives whose husbands were daily-wage workers and their income ranged from
Indian rupees 3000 (US$ 70) to 6000 (US$ 140) per month. A total of 480 women were
randomly interviewed in Tamil, the local language.
A structured questionnaire which consisted of 23 items, viz. demographic characteristics
of population, knowledge on the vector of DF, mode of transmission, behaviour of the vector
mosquito, its breeding places, biting time and water-storage practices. Data were analysed
and a simple percentage composition was used.
200
Result
The demographic characteristics of 480 women interviewed is given in Table 1. Their ages
ranged from 18 to 50 years. 63.3% of the respondents were illiterate, while 33.7% of the
respondents had gone to school (20.8% had studied up to class 5 and 12.9% had studied up
to class 12); 2.9% had a bachelor’s degree. Table 2 contains the results of the KAP study.
Table 1: Demographic characteristics of women surveyed in a
periurban area of south Chennai
Variables
Respondent
No. of women
participants
Percentage
(%)
Sex
Only female
480
Educational status
Illiterate
304
42
High school-level education
62
12.9
Higher secondary level
100
20.8
College level
14
2.9
22.08% of the respondents were aware and 77.9% were unaware of dengue fever.
Only 26% of the respondents answered that mosquito was responsible for the transmission
of dengue, the rest (73.54%) were ignorant about the mode of transmission. Knowledge
on dengue and its mode of transmission was observed to be higher among the educated
compared to the illiterate among the respondents.
2.9% of the respondents reported that rainwater and drinking water-holding containers
could be potential breeding places for the dengue-transmitting vector. The rest of the
respondents reported that drainage, garbage and stagnant dirty water could be the breeding
sites for dengue vector.
Generally, to prevent mosquito bites, 45.8% of the respondents used coils; 25.6% used
liquid vapourizers, particularly, to ward off the dengue vector; and 28.54% of them though
knew that they bit during daytime, they did not take any preventive measure.
Almost 74% of the respondents stored water in containers for their daily use and they
washed these storage containers only after three to six days. This provided a breeding place
to the mosquito. The rest of them drew water from bore-wells.
Up to 45.8% of the study subjects knew that keeping the environment clean could
prevent mosquito breeding, while 22.5% said that fogging or some other chemical method
could eradicate the mosquito population. The rest of them did not provide any answer.
201
Table 2: Knowledge, attitude and practice about dengue and its vector
S.
No.
1
2
3
4
5
6
7
202
Details
No. of women
Percentage (%)
Yes
106
22.08
No
374
77.9
Mosquito bite
127
26.04
Don’t know
353
73.5
Drinking/rainwater-holding containers
14
2.90
Dirty water, drainage, garbage
466
97.08
Mosquito coils
220
45.80
Liquid vapouriser
123
25.6
Others
137
28.5
Bite during daytime
137
28.54
Don’t know
343
71.4
Storing water in containers
356
74
Others
124
25.83
Keep environment clean
220
45.8
Fogging and chemical method
108
22.5
No response
152
31.6
Community knowledge on dengue
Mode of spread
Knowledge on dengue vector breeding
Preventive measures against mosquito biting
Knowledge on dengue vector behaviour
Water-storage practices
To eradicate the mosquito vector
The respondents were asked whether any of their family members were affected by
mosquito-borne diseases. 12.04% said their family members were affected by chikungunya,
2.01% were affected by dengue, and 1.04% were affected by malarial fever.
Discussion
Our survey showed that about three fourths (77.85%) of the respondents were unaware
about dengue and it was evident that the degree of knowledge about the disease increased
with the level of formal education. Those who had done degree-level education were
familiar with the seriousness of dengue and its mode of transmission. The same finding was
observed in another dengue study conducted in Chennai city.[4] In Delhi in 1997,87.3% of
the people were aware of dengue fever and this awareness came about due to the outbreak
of DHF in 1996.[9] But in Chennai, especially in the periurban areas (south Chennai), dengue
awareness was low because the community was not fully sensitized about dengue during
the 2001 outbreak.
Due to scarcity of water, the people in periurban areas store water for washing/drinking
purposes in plastic drums, cement tanks, cisterns, etc. These water-storage containers
are rarely washed and they form ideal breeding sites for Aedes mosquitoes. 74% of the
respondents stored water for longer periods without a proper lid. A similar situation was
observed by Kumar et al. (2010).[4] People living in periurban areas in Chennai have poor
knowledge about dengue and its mode of transmission but were somewhat aware of malaria
and its vector. To escape from mosquito bites they adopted various preventive measures but
only during the night. They could not differentiate between Anopheles and Aedes aegypti.
The respondents reported that keeping the environment clean and fogging and chemical
treatment could eradicate mosquito population; the same was observed by Ravi Kumar
and Gururaj (2006).[10] Health awareness programmes should be conducted in these areas,
especially among women who have more responsibility for household activities especially
with respect to cleanliness of the house.
Acknowledgement
We thank the University Grants Commission (UGC), New Delhi, for financial support to
carry out this research work F. No: 33-362/2007 (SR).
203
References
[1] World Health Organization. The World health report 1996: fighting disease, fostering development.
Geneva: WHO, 1997.
[2] Ramakrishnan SP, Gelfand HM, Bose PN, Sehgal PN, Mukherjee RN. The epidemic of acute haemorrhagic
fever, Calcutta, 1963: epidemiological inquiry. Indian J Med Res. 1964 Jul; 52: 633-50.
[3] Kabra SK, Verma IC, Arora NK, Jain Y, Kalra V. Dengue hemorrhagic fever in children in Delhi. Bulletin
of the World Health Organization. 1992; 70:105-108.
[4] Ashok Kumar V, Rajendran R, Manavalan R, Tewari SC, Arunachalam N, Ayanar K, Krishnamoorthi R,
Tyagi BK. Studies on community knowledge and behavior following a dengue epidemic in Chennai
City, Tamil Nadu, India. Tropical Medicine. 2010; 27(2): 330-336.
[5] Gubler DJ, Clark GG. Dengue/dengue hemorrhagic fever the empergence for a global health problem.
Emerging Infectious Disease. 1995; 1: 55-57.
[6] World Health Organization. Dengue hemorrhagic fever: diagnosis, treatment, prevention and control.
2nd edn. Geneva: WHO, 1997.
[7] Radha Krishnan J, Dhan Raj B. The problem of Dengue in Chennai. In: William John S, Vincent S,
eds. Recent trends in combating mosquitoes. Chennai: School of Entomology and Centre for Natural
Resources Management, Loyola College, 2000. pp 39-50.
[8] Vu SN, Nguyen TY, Kay BH, Marten GG, Reid JW. Eradication of Aedes aegypti from a village in Vietnam
using copepods and community participation. Am J Trop Med Hyg. 1998; 59(4): 657-60.
[9] Gupta P, Kumar P, Aggarwal OP. Knowledge, attitude and practices related to dengue in rural and slum
areas of Delhi after the dengue epidemic of 1996. J Commun Dis. 1998; 30:107-112.
[10] Ravi Kumar K and Gururaj G. Community perception regarding Mosquito borne diseases in Karnataka
state, India. Dengue Bulletin. 2006; 30: 270-277.
204
Association between dengue virus serotypes and type of
dengue viral infection in Department of Child Health,
Cipto Mangunkusumo Hospital, Jakarta, Indonesia
Dimas Seto Prasetyo,a Angky Budianti,a Beti Ernawati Dewi,a Cucunawangsih,a Roni
Chandra,a Jordan Chaidir,a Mulya Rahma Karyanti,b Hindra Irawan Satari,b Aria
Kekalih,c Ichiro Kuraned & T. Mirawati Sudiroa#
Department of Microbiology, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
a
Department of Child Health, Cipto Mangunkusumo Hospital, Faculty of Medicine Universitas
Indonesia, Jakarta, Indonesia.
b
Department of Community Medicine, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
c
d
National Institute of Infectious Diseases, Japan.
Abstract
Dengue virus infection is a major burden in Indonesia. The objective of this study was to find
the association between dengue virus serotypes and type of infection in hospitalized children in
Department of Child Health, Cipto Mangunkusumo Hospital (RSCM), Jakarta, Indonesia. A crosssectional study was conducted from 2006 to 2010 (except 2008). Blood samples from patients
diagnosed with suspected dengue infection were collected consecutively. The type of infection
was determined by dengue serology rapid tests (Panbio Dengue duo cassette and/or Bioline SD
Duo). The serotype was determined by RT-PCR. A total of 195 samples were collected. Of these,
31 (15.9%) were primary infection, 155 (79.5%) were secondary infection, and 9 (4.6%) could not
be determined. RT-PCR showed 13 (6.7%) were DENV-1; 30 (15.4%) were DENV-2; 39 (20.0%)
were DENV-3; 9 (4.6%) were DENV-4; and 5 (2.6%) were mixed infections (1 sample was DENV-1
+ DENV-2 infection, 4 were DENV-1 + DENV-3 infection); and 99 (50.8%) were negative. Among
primary infections, 22.6%, 16.1% and 6.5% of cases were caused by DENV-1, DENV-3 and DENV-2
respectively. Among secondary infections, 19.4%, 16.1%, 5.8% and 3.9% were caused by DENV-3,
DENV-2, DENV-4 and DENV-1 respectively. In this study, all four serotypes were found between
2006 and 2010. Overall, DENV-2 and DENV-3 were the predominant serotypes in hospitalized
children in the Ciptomangunkusumo Hospital, Jakarta. The majority of cases were of secondary
infections (79.5%). We found that 53.8% of DENV-1 infections were primary while all DENV-4
infections were secondary infections. Statistical analysis showed that primary infection by DENV-1
was significantly higher compared to other serotypes. Whether primary DENV-1 tends to cause
severe manifestation needs further study. More than 50% of primary and secondary dengue
infections were PCR-negative. We recommend appropriate specimen collection and handling
procedure to minimize the PCR-negative result. Continuous study is required to find the pattern
of dengue virus serotype which infects children.
Keywords: Dengue virus infection; Children; Serotype; Indonesia.
#
205
Association between dengue virus serotypes and type of dengue viral infection in Indonesia
Introduction
Dengue viral infection is a major burden in tropical and subtropical regions, including
Indonesia. Approximately 50–100 million cases occur annually in the world.[1,2] In Indonesia,
156 052 cases of dengue were reported in 2009.[3] Easier and faster transportation accelerate
the movement of infected vector and infected people.[4] Dengue virus, which consists of four
serotypes, namely, DENV-1, DENV-2, DENV-3 and DENV-4, belongs to the genus Flavivirus
of the family Flaviviridae. Aedes aegypti and Aedes albopictus are the vectors of dengue virus.
The disease can be asymptomatic or can manifest itself only as febrile symptom (dengue
fever), accompanied by headache, myalgia and, less often, a maculopapular rash.[5] Severe
manifestation, for example, haemorrhagic syndrome (dengue haemorrhagic fever) and
hypovolemic shock (dengue shock syndrome), could lead to death.[6]
In dengue-endemic areas, dengue viral infections are reported annually. When a human
is infected for the first time by one of the dengue virus serotypes, it is identified as primary
infection. Primary infection could be mild or self-limiting. It happens commonly in nonimmune children. After the first infection, they become immune to the homologous serotype.
However, during a secondary infection by a different serotype, the manifestations can be
more severe and can cause high morbidity and mortality.[7,8]
This study was undertaken to obtain epidemiological data of dengue virus serotype
which infected children in the Department of Child Health, Cipto Mangunkusumo Hospital,
Jakarta, from 2006 to 2010. It was considered important to monitor the circulating dengue
serotype in each year and find the association between the dengue virus serotype and the
type of infection.
Methods and materials
Specimen collection and serological tests
Specimens were collected from patients who were hospitalized and diagnosed by
paediatricians as cases of dengue fever (DF), dengue haemorrhagic fever (DHF) or dengue
shock syndrome (DSS) according to 1997 WHO Dengue Classification.[6] The study had been
approved by The Committee of The Medical Research Ethics of The Faculty of Medicine,
Universitas Indonesia, No. 94/PT02.FK/ETIK/2006 and 71/PT02.FK/ETIK/2009. After taking
consent, as much as 3–5 mL of peripheral blood was taken the first time a patient was
admitted to the hospital, regardless of the day of the onset of fever. The specimens were
sent to the Microbiology Laboratory Department of Microbiology Universitas Indonesia in
a cool box. Sera were separated, serologically tested and stored at –80 °C until further test
with RT-PCR.
206
In order to determine the type of infection, 10 microlitres of sera were analyzed for
anti-dengue IgM and IgG using rapid immunochromatographic test (Panbio Dengue duo
cassette and/or Bioline SD Duo) according to the manufacturer’s instructions. The results were
taken as primary infection (positive IgM and negative IgG) or secondary infection (positive
IgM and IgG or negative IgM and positive IgG). When both IgM and IgG were negative, one
more test was done before the patient was discharged. And if the result remained the same,
the positive result of NS1 antigen detection or when RT-PCR was positive, were defined as
‘indeterminate’.
NS1 antigen detection
One hundred micro litres of sera was tested for the NS1 antigen using ELISA (Panbio Inc,
Brisbane, Australia) according to the manufacturer’s manual. The results were defined as
‘positive’, ‘negative’, or ‘equivocal’. When the result was ‘equivocal’, the test was repeated
once only.
Viral RNA detection and serotype determination
Viral RNA were obtained from 140 µL sera using Viral RNA Isolation Kit (Qiagen, Gmbh, Roche,
Germany). Virus serotypes were determined using RT-PCR.[9,11] In brief, two amplification
reactions were done. In the first amplification, we used D1 and D2 primers published by
Lanciotti et al.[9] (Table 1). RNA was amplified in 25 µL mixture containing 1x PCR Buffer, 1.5
mM MgCl2, 5 pmoles of each dNTPs, D1 and D2 primers, RT-AMV (Promega) and Platinum
Taq polymerase (Invitrogen). The conditions for the first amplification were 53 °C for 30’,
denaturation at 95 °C for 5’, continued by 35-cylce of denaturation (95 °C, 45”), annealing
Table 1: Primers used for detection and serotype identification*
Primers
Sequence
Size (in bp) of amplified
DNA products (primers)
D1
5'-TCAATATGCTGAAACGCGCGAGAAACCG-3'
511
D2
5'-TTGCACCAACAGTCAATGTCTTCAGGTTC-3'
511
TS1
5'-CGTCTCAGTGATCCGGGGG-3'
482 (D1 and TS1)
TS2
5'-CGCCACAAGGGCCATGAACAG-3'
119 (D1 and TS2)
TS3
5'-TAACATCATCATGAGACAGAGC-3'
290 (D1 and TS 3)
TS4
5'-CTCTGTTGTCTTAAACAAGAGA-3'
392 (D1 and TS 4
*Modified from Lanciotti et al.[9]
207
(60 °C, 30”), and elongation (72 °C, 1’), followed by 72 °C for 7’. The second amplification
was done using 1 µL of initial amplification product. The reaction mixture contained all the
components for the initial amplification, except RT-AMV, and D2 primers were replaced by
dengue virus-spesific primer: TS1, TS2, TS3, and TS4 (Table 1). This second mixture was
conditioned at 95 °C for 5’ for denaturation, followed by 40-cycle of denaturation (95 °C,
45”), annealing (55 °C, 30”), and elongation (72 °, 1’30”), further followed by 72 °C for 7’.
Afterwards, 1 µL of amplification product was electrophoresed in 2% agarose gel and the gel
was then stained using ethidium bromide and documented using BioRad Gel Doc machine.
If there were more than one serotype in one sample, we confirmed the results by repeating
the RT-PCR once again, using serotype-specific primers in separated tubes.
Case definition and statistical analysis
Children with at least one positive result of either NS1, RT-PCR or rapid serology test were
defined as having dengue infection. Children with all negative results were excluded from
data analysis. Statistical analysis was computed using SPSS 16 Software. Comparison, among
each type of infection and association between virus serotype and type of infection were
analyzed using Fischer Exact Test.
Results
Dengue serotype
A total of 195 samples fulfilled the criteria of detection of dengue infection. Detection and
serotype determination by RT-PCR showed that 13 (6.7%) of the cases were of DENV-1; 30
(15.4%) were DENV-2; 39 (20.0%) were DENV-3; and 9 (4.6%) were of DENV-4. Mixed
infection was found in 5 (2.6%) cases, which consisted of DENV-1 + DENV-2 (1 sample)
and DENV-1 + DENV-3 (4 samples). Ninety-nine (50.8%) cases were RT-PCR-negative
(Table 2).
Type of dengue infection
The yearly data showed that within each year, secondary dengue infection predominated
(Table 2). Of the 195 samples, 9 (4.6%) were considered ‘indeterminate’. Table 2 shows
that secondary infection were found in 155 (79.5%) cases, while 31 (15.9%) were primary
infection and 9 (4.6%) were indeterminate. We compared primary and secondary infection
in each serotype (Table 3). Among primary infections, 53.8%, 12.8% and 6.7% were caused
by DENV-1, DENV-3 and DENV-2, respectively. Among secondary infections, 100%, 83.3%,
76.9% and 46.2% were caused by DENV-4, DENV-2, DENV-3 and DENV-1 respectively.
208
Table 2: Type of dengue infection
Type of infection
Year
Primary
N (%)
Secondary
N (%)
Indeterminate
N (%)
Total
2006
7 (20.0)
27 (77.1)
1 (2.9)
35
2007
6 (10.0)
50 (83.3)
4 (6.7)
60
2009
10 (21.3)
34 (72.3)
3 (6.4)
47
2010
8 (15.1)
44 (83.0)
1 (1.9)
53
Total
31 (15.9)
155 (79.5)
9 (4.6)
195
Table 3: Dengue serotype and type of infection in children
Type of infection
RT-PCR
Primary
N (%)
Secondary
N (%)
Indeterminate
N (%)
Total
DENV-1
7 (53.8)
6 (46.2)
0
13
DENV-2
2 (6.7)
25 (83.3)
3 (10)
30
DENV-3
5 (12.8)
30 (76.9)
4 (10.3)
39
DENV-4
0
9 (100)
0
9
Mix infection
1 (20)
3 (60)
1 (20)
5
Negative PCR
16 (16.2)
82 (82.8)
1 (1)
99
Total
31 (15.9)
155 (79.5)
9 (4.6)
195
Statistical analysis of dengue serotypes in primary infection
To know the association of a certain dengue serotype to hospitalized primary infection,
we did statistical analysis using Fisher’s Exact Test and its power was determined by Stata
Software Version 9 provided by the statistician. All indeterminate and negative RT-PCR results
were excluded from the calculation. First we compared among each serotype and then we
compared DENV-1 with other serotypes.
We found that more than 50% of DENV-1-positive cases were primary infection;
this was significantly higher as compared to other serotypes (p=0.001; statistical power
209
>80%). Comparisons of DENV-1 with DENV-2, DENV-1 with DENV-3, and DENV-1 with
DENV-4 also yielded significant results (p=0.002, 0.009 and 0.017 respectively). We also
found that among the hospitalized cases, secondary infection was mostly caused by other
serotypes (DENV-2, DENV-3 and DENV-4) as compared with DENV-1. Even though among
the secondary infection cases, DENV-3 was found to be more frequent than DENV-2 and
DENV-4, there was no significant difference between these serotypes (p=0.455–1.000)
and the statistical power was <60% (results not shown). In other words, we did not have
sufficient power to conclude this result. This low power was probably caused by the small
amount of samples and the number of negative PCR results.
Discussion
In this study, all four serotypes were found during the period 2006–2010. Overall, DENV-2
and DENV-3 were the predominant serotypes in hospitalized children in Ciptomangunkusumo
Hospital, Jakarta (Table 4). This result was in agreement with the reports published by
Suwandono et al.[10] and Setiati et al.[11] which also found DENV-3 as the predominant
serotype found in patients in Jakarta. A similar result was also noted in Yogyakarta,[12] though
we found that in each year, a different serotype predominated – DENV-1 in 2006, DENV-2
and DENV-3 in 2007 and 2010, and DENV-3 in 2009.
Table 4: Dengue serotypes found in child patients in 2006-2010
RT-PCR
Year
Total
2006
2007
2009
2010
DENV-1
4
0
6
3
13
DENV-2
2
16
1
11
30
DENV-3
3
16
9
11
39
DENV-4
2
0
2
5
9
Mix infection
0
0
1
4
5
Negative PCR
24
28
28
19
99
Total
35
60
47
53
195
The pathological mechanisms of DHF are still poorly understood. A number of models
have been proposed, based on epidemiological and experimental data, to explain the
pathogenesis of severe dengue illness, and, among them, is the role of intrinsic biological
properties of dengue virus strains[13] and the serotype of infecting virus in the secondary
210
infection.[14] Secondary infection was predominant in the hospitalized children. This is in
conformity with the hypothesis that secondary infection may cause more severe manifestations
because of the existence of enhancing antibodies.[15] On the other hand, some groups also
reported severe cases caused by primary infection.[14,16,17] Also, Kliks et al.[18] showed that
there was no correlation between enhancing antibodies and disease severity. A study in
the Philippines by Lim et al.[19] found that there was no significant relationship between the
severity of dengue infection based on WHO grade and irrespective of primary or secondary
infection.
We found that 15.9% of the hospitalized children had primary infection (Table 3).
Statistical analysis (Fisher’s Exact Test) showed that DENV-1 was significantly more frequent
in primary cases compared to other serotypes (p=0.001; power >80%). Several previous
reports also showed the occurrence of DENV-1 in hospitalized primary infections. A study
in Nicaragua, comparing the years when DENV-1 predominated and when DENV-2
predominated, showed that the DENV-1 season was associated with more hospitalized
primary dengue cases and more primary infections with severe manifestations.[17] A study by
Fried et al.[14] in Bangkok during 1994–2006 showed that dengue cases caused by DENV-2
and DENV-4 were all secondary infections, and there were no cases of DHF caused by
primary DENV-2 and DENV-4. Another study in Thailand by Anantapreecha et al.[20] during
1999–2002 also found that dengue cases caused by DENV-2 and DENV-4 were of secondary
infection. This was also what we found in our study that DENV-2 and DENV-4 were more
likely to develop secondary infection.
Our study showed that of DENV-1 infections, 53.8% were primary infection (Table 3),
while of DENV-2 and DENV-3, 6.7% and 12.8% respectively and none of DENV-4 were
primary infection. Among seven patients with DENV-1 primary infection, only one was below
one year of age. In the majority of these children, maternal antibody was expected to be
cleared out from the blood. These results support previous findings that there might be a
pathogenic potential of distinct DENV serotypes during primary and secondary infections.
Without previous immune priming, DENV-1 might be more pathogenic compared to other
serotypes.[14] In accordance with the pathogenicity of DENV-1, Duyen et al.[21] found that
patients in community a setting with DENV-1 primary infection had significantly higher
viral loads compared with patients with secondary DENV-1 infection, and primary DENV-1
infection was viremic significantly longer than secondary DENV-1 infection. Additionally,
more patients with primary DENV-1 infection developed haemoconcentration compared
with secondary DENV-1 infection. It also suggested that viral loads in primary infection
were significantly lower in DENV-2 and DENV-3 compared with DENV-1. However, since
our clinical data on primary infection was not sufficient for statistical analysis, we cannot
determine whether primary DENV-1 infection causes significantly severe manifestation.
Indeed, we did not conduct quantitative PCR assay to assess viral loads since the sample
was collected once, which would not be representative of peak viremia.
211
Acknowledgements
This work was, in part, funded by The Ministry of Health and Welfare, Japan, through the
National Institute of Infectious Diseases, Japan. Our gratitude to Ms Hartati, Ms Elisabeth
and Ms Ratika for their technical assistance; also to Dr Gita W. Puri and Dr Nina and nursing
staff in the Paediatrics ward for sample collection.
References
[1] Kurane I, Takasaki T. Dengue fever and dengue haemorrhagic fever: challenges of controlling an enemy
still at large. Rev Med Virol. 2001; 11: 301–11.
[2] Gubler D. Dengue virus and dengue hemorrhagic fever. Clin Microbiol Rev. 1998; 11: 480–96.
[3] World Health Organization. Situation update of dengue in the SEA Region. 2010. http://www.searo.
who.int/LinkFiles/Dengue_Dengue_update_SEA_2010.pdf - accessed 29 April 2011.
[4] Halstead SB. Epidemiology of dengue and dengue hemorrhagic fever. In: Gubler DJ, Kuno G. eds.
Dengue and dengue hemorrhagic fever. Colorado, CAB International, 1997. p. 23-44.
[5] Rothman AL. Dengue: defining protective versus pathologic immunity. J Clin Invest. 2004; 113: 94651.
Geneva: WHO, 1997.
[7] Thein S, Aung MM, Shwe TN, et al. Risk factors in dengue shock syndrome. Am J Trop Med Hyg.
1997; 56:566-72.
[8] McBride WJH, Bielefeldt-Ohmann H. Dengue viral infections; pathogenesis and epidemiology. Microbes
Infect. 2000; 2:1041-50.
[9] Lanciotti RS, Calisher CH, Gubler DJ, Chang GJ, Vorndam AV. Rapid detection and typing of dengue
viruses from clinical samples by using reverse transcriptase-polymerase chain reaction. J Clin Microbiol.
1992 Mar; 30(3): 545-551.
[10] Suwandono A, Kosasih H, Nurhayati, Kusriastuti R, Harun S, Ma’roef C, Wuryadi S, Herianto B, Yuwono
D, Porter KR, Beckett CG, Blair PJ. Four dengue virus serotypes found circulating during an outbreak
of dengue fever and dengue haemorrhagic fever in Jakarta, Indonesia, during 2004. Trans R Soc Trop
Med Hyg. 2006 Sep; 100(9): 855-62.
[11] Setiati TE, Wagenaar JFP, de Kruif MD, Mairuhu ATA, van Gorp ECM, Soemantri A. Changing
epidemiology of dengue haemorrhagic fever in Indonesia. Dengue Bulletin. 2006; 30:1-14.
[12] Graham RR, Juffrie M, Tan R, Hayes CG, Laksono I, Ma’roef C, Erlin, Sutaryo, Porter KR, Halstead SB.
A prospective seroepidemiologic study on dengue in children four to nine years of age in Yogyakarta,
Indonesia I. studies in 1995-1996. Am J Trop Med Hyg. 1999; 61(3): 412-419.
[13] Rico-Hesse R, Harrison LM, Salas RA, et al. Origins of dengue type 2 viruses associated with increased
pathogenicity in the Americas. Virology. 1997; 230: 244–51.
212
[14] Fried JR, Gibbons RV, Kalayanarooj S, Thomas SJ, Srikiatkhachorn A, Yoon IK, Jarman RG, Green S,
Rothman AL, Cummings DA. Serotype-specific differences in the risk of dengue hemorrhagic fever:
an analysis of data collected in Bangkok, Thailand from 1994 to 2006. PLoS Negl Trop Dis. 2010 Mar
2;4(3):e617.
[15] Laoprasopwattana K, Libraty DH, Endy TP, Nisalak A, Chunsuttiwat S, Vaughn DW, et al. Dengue virus
(DV) enhancing antibody activity in preillness plasma does not predict subsequent disease severity or
viremia in secondary DV infection. The Journal of Infectious Diseases. 2005; 192(3): 510-9.
[16] Vaughn DW, Green S, Kalayanarooj S, Innis BL, Nimmannitya S, Suntayakorn S, Endy TP, Raengsakulrach
B, Rothman AL, Ennis FA, Nisalak A. Dengue viremia titer, antibody response pattern, and virus serotype
correlate with disease severity. J Infect Dis. 2000; 181: 2-9.
[17] Balmaseda A, Hammond SN, Pérez L, Tellez Y, Indirasaborío S, Mercado JC, et al. Serotype-specific
differences in clinical manifestations of dengue. Am J Trop Med Hyg. 2006; 74(3): 449-456.
[18] Kliks SC, Nisalak A, Brandt WE, Wahl L, Burke DS. Antibody-dependent enhancement of dengue
virus growth in human monocytes as a risk factor for dengue hemorrhagic fever. Am J Trop Med Hyg.
1989; 40: 444-51.
[19] Lim JG, Gatchalian SR, Capeding MRZ. Profile of pediatric patients with dengue fever/dengue
hemorrhagic fever over: a five-year period (2000-2004). PIDSP Journal. 2010; 11(1): 26-34.
[20] Anantapreecha S, Chanama S, Anuegoonpipat A, Naemkhunthot S, Sangasang A, et al. Serological and
virological features of dengue fever and dengue haemorrhagic fever in Thailand from 1999 to 2002.
Epidemiol Infect. 2005; 133(3): 503-507.
[21] Duyen HTL, Ngoc TV, Ha DT, Hang VTT, Kieu NTT, Young PR, et al. Kinetics of plasma iremia and
soluble nonstructural protein 1 concentrations in dengue: differential effects according to serotype
and immune status. J Infect Dis. 2011 May 1; 203(9):1292-300.
213
Short Note
Study of prevalent practices about use of platelets in
management of dengue cases in selected tertiary care
hospitals in Delhi in 2009
K.N. Tewari,a# N.R. Tulib & S.C. Devganc
Public Health Consultant and former Municipal Health Officer, Municipal Corporation of Delhi,
New Delhi, India.
a
Dy. Health Officer, Municipal Corporation of Delhi, New Delhi, India.
b
Consultant and formerly Head of Dept. of Medicine, Hindu Rao Hospital, Delhi.
c
Dengue has been reported from Delhi since 1967. Subsequently, regular and frequent dengue
outbreaks were recorded in Delhi from 1996 to 2006. The 1996 outbreak was the most
serious, which resulted in 10 252 hospitalizations with 423 deaths. Dengue fever is now
endemic in Delhi as all four serotypes (DENV-1 to DENV-4) are circulating in the city.[1]
As per media reports, the demand for platelet transfusion for the management of DF/DHF
has increased substantially, especially during the outbreaks. In this context, it was considered
desirable to generate scientific evidence on platelet transfusion, as there are inherent risks
associated with the transfusion of blood/blood products.
During 2009, a retrospective and observational study was carried out in Delhi. Data was
collected in respect of 230 cases from the records of three private tertiary care hospitals and
one hospital run by the Municipal Corporation of Delhi, all situated at different locations in
the city. Data is limited to cases admitted only during 7–25 December 2009.
These cases were selected based on completeness of records, i.e. they had clinical and
lab investigation records, information about their management once they were serologically
confirmed, and these cases were duly notified by the Municipal Corporation of Delhi (Source:
Municipal Corporation of Delhi).
As per WHO guidelines, dengue virus infection may be asymptomatic or may cause
undiffrentiated febrile illness (viral syndrome) dengue fever and dengue haemorrhagic
fever / dengue shock syndrome. DF is commonly benign, is defined as acute febrile illness
with two or more manifestations, i.e. headache, retro-orbital pain, myalgia, arthralgia.[2]
Haemorrhagic manifestations like skin haemorrhage with tourniquet test and/or petechiae
#
214
Study of prevalent practices about use of platelets in management of dengue cases in Delhi
are common. There have also been reports of epistaxis, gingival bleeding, gastrointestinal
bleeding, haematuria and hypermenorrhagia.[3] DF complicated by unusual haemorrhage
and thrombocytopaenia must be differentiated from DHF. Haemorrhage DHF is defined
as 2-7-days’ acute febrile illness with bleeding, thrombocytopenia, an evidence of plasma
leakage and a rise in haematocrit to or greater than 20% above the average. When all
the features of DHF are present along with evidence of circulatory failure, the patient is
categorized as DSS.[2]
In all, 230 cases were identified as of dengue as per WHO guidelines (Table).[3] Of these,
163 were classified as of dengue fever, diagnosed on the basis of clinical signs and symptoms
and where there was no plasma leakage. Of these, 138 were primary dengue cases without
haemorrhagic plasma leakage, while 57 patients were given platelet transfusion. Out of
25 cases with haemorrhagic manifestations, 22 were given platelet transfusion. Dengue
haemorrhagic fever (DHF) cases (n=67) were further categorized into grades I to IV – 51
cases qualified for Grade I, 13 for Grade II and 3 cases for Grade III; none qualified for
Grade IV. Out of the 67 DHF cases, 50 were given platelet transfusion; these included 40,
8 and 2 cases of DHF grade I, II and III, respectively.
Table: Cases of dengue viral infection and cases given platelet transfusion (n=230)
S.
No.
Category
No. of
cases
No. of cases
given platelet
transfusion
(%)
Criteria
1.
DF
163
79 (48.5)
Clinical presentation
a.
Primary dengue
138
57 (41.3)
Dengue without
haemorrhagic manifestations
b.
Primary dengue
with haemorrhagic
manifestations
25
22 (88.0)
All cases of bleeding without
any evidence of plasma
leakage
2
DHF
67
50 (74.6)
Cases of bleeding with
evidence of plasma leakage
a.
DHF grade I
51
40 (78.4)
Positive tourniquet test with
evidence of plasma leakage
b.
DHF grade II
13
8 (61.5)
As in grade I plus
spontaneous bleeding
c.
DHF grade III
3
2 (66.6)
As in grade I and II plus
circulatory failure
d.
DHF grade IV (DSS)
0
0
As in grade III plus profound
shock
215
Study of prevalent practices about use of platelets in management of dengue cases in Delhi
The analysis of cases showed that all patients of DF (163) were treated with crystalloids;
of these 79 patients (48.5%) were given platelet transfusion also. Of the 67 cases of DHF,
50 cases (74.6%) were given platelet transfusion.
All units of blood products are screened for transfusion-transmissible infections, viz. HIV,
hepatitis B and hepatitis C.
Conclusion
In our study, we found that for the management of DF/DHF cases, platelet count was been
done more frequently than finding serial haematocrit value for prognosis and effective
management. It was observed that transfusions were done on more cases than was necessary
as per WHO guidelines. Platelet transfusions were resorted largely due to the attending
clinician’s concern about the outcome of treatment.
Acknowledgments
We are grateful to Dr J.P. Narain, Director, Communicable Diseases, WHO-SEARO, for his
motivation and encouragement to do this study. We are also thankful to Dr Rajesh Bhatia,
Regional Adviser (Blood Safety and Laboratory Technology), WHO-SEARO, for his advice to
incorporate platelet transfusion in our work. Our sincere thanks to Dr Om Prakash Gahlot
and medical record officers of concerned hospitals, without whose support it would not
have been possible to complete this study.
References
[1] Guidelines for Prevention and Control of Dengue. Zoonosis Division, National Institute of Communicable
Diseases (Directorate General of Health Services) 22-Sham Nath Marg, Delhi- 110 054, 2006. http://
www.whoindia.org/LinkFiles/Communicable_Diseases_Guidelines_for_Prevention_and_Control_
Dengue_Haemorrhagic_Fever.pdf.
[2] World Health Organization. Dengue haemorrhagic fever: diagnosis, treatment, prevention and control,
2nd edition. Geneva, World Health Organization, 1997.
[3] World Health Organization. Comprehensive guidelines for prevention and control of dengue and
dengue haemorrhagic fever. Revised and expanded edition 2011 (SEARO Technical Publication Series
No. 60), Regional Office for South East Asia, New Delhi.
216
Short Note
Demographic features of imported dengue fever and
dengue haemorrhagic fever in Japan from 2006 to 2009
Tomohiko Takasaki,# Akira Kotaki, Shigeru Tajima, Tsutomu Omatsu, Fumiue
Harada, Chang-Kweng Lim, Meng Ling Moi, Mikako Ito, Makiko Ikeda & Ichiro
Kurane
Department of Virology 1, National Institute of Infectious Diseases, Toyama 1-23-1, Shinjuku-ku,
Tokyo 162-8640, Japan.
Dengue virus infections are a major public health problem in tropical and subtropical countries
in the world.[1,2] In Japan, dengue was endemic in the subtropical island of Okinawa from
1893.[3] On the temperate mainland there were a series of outbreaks from 1942 to 1945.
Dengue fever emerged in Nagasaki city in August 1942 and soon spread to other cities such
as Sasebo, Hiroshima, Kobe and Osaka and recurred every summer until 1945.[4] Although
there have been no reports of dengue outbreaks in mainland Japan or Okinawa since 1945,
there have bee n many imported dengue cases.[5] Dengue fever (DF) / dengue haemorrhagic
fever (DHF) is listed as one of the Category IV notifiable infectious diseases under the
Infectious Diseases Control Law of Japan. A high percentage of reported dengue cases have
been confirmed by laboratory tests. In the present study, the demographic features of the
imported DF/DHF cases that were confirmed by laboratory tests from 2006 to 2009 were
analysed at the Vector-Borne Virus Laboratory, Department of Virology 1, National Institute
of Infectious Diseases (NIID), Japan.
Blood specimens from 419 suspected dengue cases from the years 2006 to 2009 were sent
to our laboratory for laboratory diagnosis. From these, 191 were confirmed as dengue virus
infection. As shown in Table 1, these include 29 cases in 2006; 51 in 2007; 67 in 2008 and
44 cases in 2009. The rate of confirmation among these clinically-suspected cases was 46%.
Infecting dengue virus serotypes were determined for 137 cases by real-time RT-PCR
(TaqMan).[6] The number of cases infected with each of the four dengue virus serotypes were
as follows: 48 (35%) with type 3, 45 (33%) with type 1, 28 (20%) with type 2, and 16 (12%)
with type 4 (Table 2). Interestingly, there were no cases of dengue virus type 4 infection in
2006 and there was only one in 2007. Age distribution was a nalysed for 187 of the 191
cases (Table 3). Patient age was unknown in the remaining 4 cases. From these cases, 143
(77%) were 20-49 years of age; 70 (37%) were 20-29 years; 43 (23%) were 30-39 years; and
30 (16%) were 40-49 years. Regarding gender in the 189 cases where it was known, 63%
of the cases were male and 37% were female (Table 4). The monthly distribution of dengue
infections was also analysed (Table 5). Although dengue cases were in all 12 months of the
#
217
Demographic features of imported DF and DHF in Japan
Table 1: Number of investigated DF/DHF cases and results of analysis , Japan, 2006-2009
Cases examined and confirmed in NIID
Examined
Confirmed
Positive rate (%)
Official number of
reported cases in
Japan
2006
100
29
29
58
2007
104
51
49
89
2008
129
67
52
104
2009
86
44
51
88
Total
419
191
46
339
Year
All cases were officially reported in Japan and laboratory confirmed by Department of Virology 1, National Institute of
Infectious Diseases.
Table 2: Virus serotypes from confirmed dengue cases, Japan, 2006-2009
Dengue virus type
2006
2007
2008
2009
Total (%)
Type 1
10
10
17
8
45 (33%)
Type 2
1
5
9
13
28 (20%)
Type 3
9
16
16
7
48 (35%)
Type 4
0
1
7
8
16 (12%)
Total
20
32
49
36
137
Table 3: Age-wise distribution of dengue cases, Japan, 2006-2009
Age
Year
Total
2006
2007
2008
2009
0–9
1
2
1
0
4
10–19
5
3
3
1
12
20–29
10
24
22
14
70
30–39
4
9
14
16
43
40–49
6
8
9
7
30
50–59
1
4
9
3
17
60
1
1
8
1
11
Unknown
1
0
1
2
4
Total
29
51
67
44
191
218
year, the majority (nearly 60%) of the infections occurred between July and October. There
were 20 cases reported in the month of July, 29 each in August and September, and 27
in October. In Japan, July to September is a period in which many people have a summer
vacation and many travellers tend to visit dengue-endemic areas. Furthermore, according to
Japanese Emigration and Immigration Management, about 40% of immigration is recorded
from July to September.
Regarding the suspected sources of infection, 180 cases (86%) were returnees or visitors
from South-East Asia and South Asia; 12 (6%) had come from Pacific islands, 9 (4%) came
from Central America and 7 (3%) had returned from South America. The one reported case
from Africa was a returnee who had stayed in Cote d’Ivoire for one month (Table 6).[7]
Table 4: Male-female ratio of dengue cases, Japan, 2006-2009
Sex
Year
Total
2006
2007
2008
2009
Male
20
33
39
26
118
Female
9
18
27
17
71
Unknown
0
0
1
1
2
Total
29
51
67
44
191
In 2006, the number of male overseas travellers was 9.92 million and the number of female overseas travellers was
7.62 million (ratio 56:44).
Table 5: Monthly distribution of dengue cases, Japan, 2006-2009
Month
Year
Total
2006
2007
2008
2009
Jan
1
0
2
5
8
Feb
0
3
7
4
14
Mar
3
4
2
0
9
Apr
5
5
1
2
13
May
1
3
6
3
13
Jun
2
3
4
0
9
Jul
4
7
7
2
20
Aug
2
10
10
7
29
Sep
3
5
12
9
29
Oct
2
6
9
10
27
Nov
1
3
6
0
10
Dec
5
2
1
2
10
Total
29
51
67
44
191
219
Table 6: Travel destinations of dengue cases, Japan, 2006-2009
Destination
2006
2007
2008
2009
Total cases
2
9
1
4
2
3
1
0
1
2
0
0
1
0
0
0
15
9
3
5
3
2
5
1
2
0
1
0
0
0
0
0
9
7
12
17
7
4
3
3
0
1
2
1
4
1
1
0
7
3
10
2
4
3
1
1
1
1
0
0
0
2
0
1
180 (86%)
33
28
26
28
16
12
10
5
4
4
3
1
5
3
1
1
Pacific islands
Samoa
Papua New Guinea
Tahiti
Tonga
Tuvalu
Vanuatu
Solomon Islands
3
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
1
0
1
0
1
2
2
0
1
0
12 (6%)
3
2
2
2
1
1
1
Central America
Honduras
Central America*
Panama
Mexico
Jamaica
0
0
0
0
0
1
1
0
0
3
1
0
0
0
1
0
0
1
1
0
9 (4%)
2
1
1
1
4
South America
Brazil
Bolivia
3
0
2
1
0
0
0
1
7 (3%)
5
2
Africa
Cote d'Ivoire
0
0
1
0
1 (0.5%)
1
Asia
Indonesia
Philippines
India
Thailand
Viet Nam
Malaysia
Cambodia
Singapore
Bangladesh
Timor-Leste
Myanmar
Lao PDR
Maldives
Sri Lanka
Pakistan
Yemen
Some patients visited more than one country.
*The patient visited three Central American countries .
220
Worldwide, it is estimated that Figure: Officially reported dengue cases in Japan,
each year there are up to 100 million
2006-2009
DF cases and 250 000 DHF cases,
120
and these epidemics ha ve been
104
[8]
expanding. In recent years, dengue
100
92
89
outbreaks have been an annual
80
74
occurrence in Taiwan,[9] and dengue
58
60
virus endemicity was confirmed for
50 52
49
the first time in Nepal.[10] Each year,
40
32
nearly 11 million Japanese people
18
20
9
visit tropical and subtropical areas and
0
about two million people visit Japan
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
from these areas. In the past decade,
the number of imported dengue cases All dengue cases were imported. There were no cases of
has increased year upon year (Figure). domestic infection during this period.
Dengue epidemic s often occur in
urban areas because residential areas are common breeding sites for Aedes aegypti, the
major vector of DF/DHF. Growing urbanization in dengue-endemic regions has resulted
in dengue epidemics occurring with greater frequency. Because the majority of Japanese
travellers abroad visit urban rather than rural areas, there is a need for closer surveillance of
DF/DHF in Japan. Information on dengue should be provided to travellers to tropical and
subtropical areas.
Acknowledgments
This work was supported by Research on Emerging and Re-emerging Infectious Diseases
(H20-shinkou-ippan-013, H20-shinkou-ippan-015 and H21-shinkou-ippan-005) department
of the Ministry of Health, Labour and Welfare, Japan.
References
[1] Halstead SB. Pathogenesis of dengue: challenges to molecular biology. Science 1988;239 (4839):47681.
[2] Kurane I, Takasaki T. Dengue fever and dengue haemorrhagic fever: challenges of controlling an enemy
still at large. Rev Med Virol 2001;11(5):301-11.
[3] Tadano M, Okuno Y, Fukunaga T, Fukai K. Retrospective serological studies on dengue epidemics in
Osaka and Okinawa. Biken J 1983;26(4):165-7.
[4] Hotta S. Twenty years of laboratory experience with dengue virus. In: Saunders M and Lennette EH
(ed.), Medical and Applied Virology. Geen, St Louis, 1965, 228-256.
221
[5] National Institute of Infectious Diseases and Tuberculosis and Infectious Diseases Control Division,
Ministry of Health, Labour and Welfare. Imported dengue and dengue hemorrhagic fever in Japan, as
of July 2007. IASR, Vol.28, No.8, pp. 213-214, 2007.
[6] Ito M, Takasaki T, Yamada K, Nerome R, Tajima S, Kurane I. Development and evaluation of fluorogenic
TaqMan reverse transcriptase PCR assays for detection of dengue virus types 1 to 4. J Clin Microbiol
2004;42(12):5935-7.
[7] ProMed-mail. Dengue/DHF update: Japan ex Cote d’Ivoire. ProMed-mail 2008; 18 Aug:
20080818.2573. <http://www.promedmail.org>. Accessed 18 August, 2008.
World Health Organization, 2nd edition. Geneva, 1997, 12-23.
[9] Lee IK, Liu JW, Yang KD. Clinical and laboratory characteristics and risk factors for fatality in elderly
patients with dengue hemorrhagic fever. Am J Trop Med Hyg 2008,79(2):495-505.
[10] Takasaki T, Kotaki A, Nishimura K, Sato Y, Tokuda A, Lim CK, Ito M, Tajima S, Nerome R, Kurane I.
Dengue virus type 2 isolated from an imported dengue patient in Japan: first isolation of dengue virus
from Nepal. J Travel Med 2008;15(1):46-49.
222
Short Note
Evaluating school students’ perception about
mosquitoes and mosquito-borne diseases
in the city of Kolkata, India
D. Biswas,a# Baishakhi Biswas,a Bithika Mandal,a A. Banerjee,a
T.K. Mukherjeea & J. Nandib
Vector Control Department, Kolkata Municipal Corporation, 149 A.J.C. Bose Road,
Kolkata–700014, India.
a
Directorate of National Vector Borne Disease Control Programme, Government of India,
22 Sham Nath Marg, Delhi–110054, India.
b
Introduction
Kolkata, the Capital of the Indian state of West Bengal, is located at the intersecting point of
latitude 22˚ 33’ 47” N and longitude 88˚ 23’ 34” E; it sprawls over an area of 187.5 sq km
and is inhabited by 4 486 679 people. The area of Kolkata Municipal Corporation (KMC) is
divided into 15 boroughs consisting of a total of 141 wards. Three meteorologically distinct
seasons –hot summer, rainy period and winter – characterize the climate of the city.
Malaria is an age-old public health problem in the city. According to a report, the
transmission of malaria has been going on in Kolkata since its establishment back in 1690.[1]
According to a report of the Integrated Disease Surveillance Programme (IDSP) wing of the
KMC, 59 700 people suffered from malaria during the period 2000–2010. Of them, 7912
people (13.2%) suffered from falciparum malaria and the rest (86.7%) from vivax malaria.
Due to increased environmental conduciveness and other favourable factors, transmission
of malaria has now become an annual feature.
Dengue is also endemic in Kolkata. All the four serotypes of dengue virus (DENV-1–4)
are circulating in the city.[2] An epidemic of DHF occurred in July 1963 when 100 000 people
were infected, most of them were children. Five hundred patients were admitted to hospitals,
of whom 200 died.[3-6] Since then, DF/DHF continues to occur annually.
Besides malaria and dengue, cases of chikungunya are also reported in Kolkata.[7] The
city is also endemic for the crippling ailment of bancroftian filariasis.[8].
#
E-mail: [email protected], [email protected]
223
School students’ perception about mosquitoes and mosquito-borne diseases in Kolkata
Strategies for prevention and control of malaria and DF/DHF
•
Early diagnosis and prompt treatment of malaria through 136 malaria clinics situated
in 131 wards of the city.
•
Providing facilities for detection of dengue by ELISA-based technique through five
clinics.
•
Recurrent anti-larval measures through conventional larvicides as per the policy of
the National Vector-Borne Disease Control Programme (NVBDCP).
•
Minor engineering methods such as source reduction, de-weeding, etc.
•
Biological control through larvivorous fish at appropriate breeding sites.
•
Space spray as emergency response to control infective disease vectors.
Supportive interventions
A strong and sustained information, education and communication (IEC) campaign for
creating community awareness and their involvement should include:
•
Distribution of printing materials
•
Insertions in newspapers
•
Displaying posters and banners at health camps
•
Broadcasting through television and radio
•
Information on mosquitoes, malaria and dengue should be regularly and widely
published in leading newspapers during the season of high transmission of malaria
and dengue.
To assess the effectiveness of IEC activities among schoolchildren, a survey was conducted
by the Vector Control Department of the Kolkata Municipal Corporation in November–
December 2009. The survey covered 414 students belonging to 14–16 years age group
from six schools (four Bengali medium and two English medium schools). All these students
were studying in Class X and were from the same socioeconomic group. No public health
educational programme had been undertaken by the school authorities. A questionnaire
containing 28 questions, having three options for each, was circulated.
Evaluation result
The answers given by the students were quite intriguing (Table 1). Of the 414 students
tested, 290 (70%) were aware that it is the female mosquito that bites and thus transmits a
disease. 48% of students were not aware that a mosquito is a 6-legged creature. The fact of
mosquitoes identifying their blood hosts by smelling the body odour was known to 55% of
224
Table 1: Questionnaire with correct responses received from students of class X of four
schools in Kolkata during November–December 2009
S.
No.
1.
2.
3.
4.
5.
6.
7.
8.
Questions asked
Options given against the
question
No. & choice of
students
(in percentage)
No.
%
Among mosquitoes,
which one bites, male or
female?
A. Male
60
14.5
B. Female
290
70
C. Both
64
15.5
How many legs does a
mosquito have?
A. 2 legs
73
17.6
B. 4 legs
125
30.2
C. 6 legs
216
52.2
How does a female
mosquito identify her
prey?
A. Seeing
120
30.0
B. Smelling
228
55.1
C. Hearing
66
15.9
Through which part of its
body a mosquito spreads
disease?
A. Wing
30
7.2
B. Leg
58
14.0
C. Proboscis
326
78.7
Where do mosquitoes
lay eggs?
A. Stagnant water
341
82.4
B. Heaps of garbage
65
15.7
C. Dark corners of bedrooms
8
1.9
Where do mosquito
larvae breathe in oxygen
from?
A. Air
60
14.5
B. Water
250
60.4
C. Both
104
25.1
How many days does
a mosquito require to
complete its life-cycle?
A. 30 days
63
15.2
B. 15 days
188
45.4
C. 7 days
163
39.4
How many stages are
involved in the life-cycle
of a mosquito?
A. 2 stages (i.e. egg and adult)
83
20.0
B. 3 stages (i.e. egg, larva and
adult)
128
30.9
203
49.0
C. 4 stages (i.e. egg, larva, pupa
and adult)
225
S.
No.
9.
10.
11.
12.
13.
Questions asked
question
No. & choice of
students
(in percentage)
No.
%
Which species of
mosquitoes in Kolkata
outnumbers others?
A. Armigeres subalbatus
52
12.6
B. Aedes albopictus
196
47.3
C. Culex quinquefasciatus
166
40.1
Which mosquito
commonly breeds in
the polluted water of
the Beliaghata Circular
Canal and Tolly’s Nullah
of Kolkata?
A. Anopheles sp.
221
53.4
B. Aedes sp.
102
24.6
C. Culex sp.
91
22.0
Which mosquito
commonly breeds in
septic tanks?
A. Armigeres sp.
57
13.8
B. Culex sp.
245
59.2
C. Anopheles sp.
112
27.1
What is the most
appropriate way of
combating mosquito
menace?
A. Fogging
85
20.5
B. Indoor residual spraying
24
5.8
C. Destruction of breeding sites
305
73.7
Name the best way of
preventing mosquito
breeding in domestic
water containers.
A. Emptying them at weekly
intervals
195
47.1
B. Treating them with
insecticides
150
36.2
69
16.7
C. Covering them with tight lids
14.
15.
16.
226
Which fish is commonly
used for destroying
mosquito larvae?
A. Lata
110
26.6
B. Guppy
204
49.3
C. Tilapia
100
24.2
Name the poisonous
gas emitted along with
the smoke of an antimosquito coil.
A. Methane
115
27.8
B. Carbon monoxide
218
52.7
C. Ammonia
81
19.6
Malaria is spread by
mosquitoes; who
discovered this?
A. Charles Darwin
96
23.2
B. Sir Ronald Ross
188
45.4
C. Alfanso Laveran
130
31.4
S.
No.
17.
18.
19.
Questions asked
question
21.
22.
23.
24.
25.
No.
%
Which disease killed
many companions of Job
Charnock#?
A. Dengue
125
30.2
B. Encephalitis
72
17.4
C. Malaria
217
52.4
Which species of
mosquitoes spreads
malaria in Kolkata?
A. Anopheles subpictus
87
21.0
B. Anopheles stephensi
187
45.2
C. Aedes albopictus
140
33.8
What is the prime cause
of a malarial death?
A. Delayed treatment
232
56.0
B. Non-availability of treatment
facilities
132
31.9
50
12.1
C. Ineffectiveness of medicine
20.
No. & choice of
students
(in percentage)
Name the parasite
among the three that
causes uncomplicated
malaria
A. Entamoeba histolytica
107
25.8
B. Plasmodium vivax
192
46.4
C. Escherichia coli
115
27.8
Which one among these
three medicines is used
for radical treatment of
malaria?
A. Crocin
29
7.0
B. Aspirin
106
25.6
C. Primaquine
279
67.4
From which part of a
cinchona tree is quinine
derived?
A. Flower
20
4.8
B. Bark
364
87.9
C. Root
30
7.2
To prevent malaria,
which one do you
consider most effective?
A. Ordinary mosquito net
180
43.5
B. Mosquito repellents
92
22.2
C. Insecticide-treated mosquito
nets
142
34.3
Which disease is
commonly called
“Break-bone fever”?
A. Malaria
180
43.5
B. Filariasis
94
22.7
C. Dengue
140
33.8
When does the denguebearing species Aedes
aegypti bite?
A. Day
168
40.6
B. Night
175
42.3
C. Round the clock
71
17.1
227
S.
No.
26.
27.
28.
Questions asked
question
No. & choice of
students
(in percentage)
No.
%
Where does Aedes
aegypti commonly breed
in Kolkata?
A. Masonry tank
208
50.2
B. Overhead water tank
144
34.8
C. Tree-hole
62
15.0
Name the causative
agent of dengue
A. Bacteria
289
69.8
B. Virus
28
6.8
C. Worm
97
23.4
A. Aedes aegypti
112
27.0
B. Anopheles vagus
165
39.9
C. Anopheles hyrcanus
137
33.1
Name the principal
vector of chikungunya
Job Charnock (1630-1693), who was until recently considered to be the founder of Calcutta (now Kolkata), was a
British merchant. He came to India in 1655-1656 and initially settled in an area called Cossimbazar near Kolkata.
In 1686, he came to Hooghly as the Chief Agent of East India Company. Then, in 1690, he clubbed Kalikata,
Gobindapur and Sutanuti together and named it Calcutta. According to a report in Your Health[1], many companions
of Job Charnock died of malaria in Kolkata in a span of only one year after their arrival in the city.
#
the students. More than 78% of them knew the name of the appendage by which a mosquito
sucks blood. Where does a female mosquito lay her eggs? The right answer (stagnant water)
was known to 82.3% of them. Interestingly, 85.5% of them were not aware that though
mosquito larvae are aquatic, they, unlike fish, inhale oxygen from the air and not from the
water. More than 60% students were not aware that the life-cycle of a mosquito completes in
a week and that the life-cycle comprises four stages (i.e. egg, larva, pupa and adult) was not
known to even half of them. In Kolkata, Culex quinquefasciatus outnumbers other species of
mosquitoes. Surprisingly, 60% of the students were not aware of this. About 80% even failed
to say that this vector species together with the other species of Culex, commonly breeds
in the polluted water of the widely-known Beliaghata Circular Canal and Tolly’s Nullah of
the city. Which mosquito commonly breeds in septic tanks? The answer to this question
was known to merely 14% respondents. Nearly 74% of them knew that mosquitoes could
be best controlled by destroying their breeding sites. Only 47.1% students rightly said that
mosquito breeding in domestic water containers could be prevented by emptying them at
weekly intervals. Again, only 49.3% students knew that the larvivorous fish “guppy” (Poecilia
reticulata) is commonly used for destroying mosquito larvae. More than 50% students knew
that carbon monoxide is emitted in the smoke of anti-mosquito coils that the people of
Kolkata often use to prevent mosquito-bites.
228
Malaria is an age-old problem in Kolkata. But, sadly, about 55% of students failed to tell
that the Nobel laureate, Sir Ronald Ross, discovered that malaria is vectored by mosquitoes.
It is also said that many companions of Job Charnock, who was until recently considered
the founder of the city of Kolkata, succumbed to malaria in a span of only one year after
their arrival in the city. Thankfully, more than 50% of students were aware of this story.
But half of the students could not tell that Anopheles stephensi was the vector of malaria
in Kolkata. As many as 232 students (56%) rightly said that death due to malaria occurred
primarily due to delayed treatment. But Plasmodium vivax, the parasite responsible for
causing uncomplicated malaria, was not known to about 55% of them. That primaquine is
a drug meant for curing malaria was known to 67%. Of the 414 students interviewed, 364
(87.9%) knew that quinine is derived from the bark of cinchona trees. Interestingly, 34%
students rightly said that the transmission of malaria could be effectively prevented by using
insecticide-treated bednets (ITNs).
Dengue, commonly called the ‘break-bone’ fever, was known to only 34% of the students.
Similarly, the fact that Aedes aegypti is a day-biter was known only to 40.6% respondents.
But, thankfully, almost half of the students were aware that Aedes aegypti primarily breeds
in masonry tanks in Kolkata. About 68% of them knew that dengue is a viral disease. Clearly,
though the students were quite knowledgeable about dengue, their perception about its
vector was disappointing.
A single fundamental question asked concerning chikungunya was about its principal
vector. The correct answer was known only to 27% participants.
Conclusion
Our evaluation showed that student awareness about mosquito-borne diseases and its control
was not satisfactory; therefore, the Kolkata Municipal Corporation took steps to improve the
situation. These included:
•
One of the actions taken was the publication of multicoloured booklets entitled
“Mosquito-borne diseases in Kolkata and their prevention” in four languages (150 000
copies in Bengali, 100 000 in English, 50 000 in Hindi and 25 000 in Urdu), exclusively meant for students. It was distributed in 700 schools the students of as many
as 699 schools of the city free of cost.
The idea of planning and conducting such an awareness campaign was derived from
a publication of the World Health Organization.[9] In this booklet, basic information about
malaria, dengue, chikungunya and bancroftian filariasis has been provided, together with
some useful tips on the prevention and control of mosquito breeding, which students could
undertake by themselves and also involve the community as a whole.
229
Acknowledgements
The authors thankfully acknowledge the support and encouragement given by Mr Atin Ghosh,
Honourable Member of the Mayor-in-Council (Health) of Kolkata Municipal Corporation. The
assistance provided by the staff of the Vector Control Department and the IDSP wing of KMC
in collecting epidemiological information about malaria and dengue is much appreciated.
References
[1] Hati AK, Mukherjee H, Chandra G, Bhattacharya J, Chatterjee KK, Banerjee A, Biswas D and Halder
S. Vector-borne diseases in urban community. Your Health 1991;40(7):157-158.
[2] Mukherjee KK, Chakraborty SK, Dey PN, Dey S and Chakraborty MS. Outbreak of febrile illness due
to dengue virus type 3 in Calcutta during 1983. Trans Roy Soc Trop Med Hyg 1987;81:1008-1010.
[3] Verchere AM. Report on the epidemics of dengue of 1872, as it appeared in Fort Williams, Calcutta.
Indian Med Gaz 1879;14:91-95.
[4] Seal SC. Epidemiology of dengue and haemorrhagic fever. Bull Calcutta School Trop Med 1981;29:106111.
[5] Ramakrishna SP, Gelfand HM, Bose PN, Sehgal PN and Mukherjee RN. The epidemic of acute
haemorrhagic fever Calcutta, 1963 : Epidemiological inquiry. Indian J Med Res 1964; 52:1-18.
[6] Sarkar JK, Chatterjee SN and Chakraborty SK. Three-year study of mosquito-borne haemorrhagic fever
in Calcutta. Trans Roy Soc Trop Med Hyg 1967; 61: 725-735.
[7] Bandyopadhyay B, Bandyopadhyay D, Bhattacharya R, De R, Saha B, Mukherjee H and Hati AK. Death
due to chikungunya. Trop Doct 2009; 39 (3): 187-188.
[8] Hati AK, Chandra G, Bhattacharya A, Biswas D, Chatterjee KK and Dwibedi HN. Annual transmission
potential of bancroftian filariasis in an urban and rural area of West Bengal, India. Am J Trop Med Hyg
1989; 40 (4): 365-367.
[9] Will Parks and Linda Lloyd. Planning social mobilization and communication for dengue fever prevention
and control: a step-by-step guide. WHO 2004. WHO Mediterranean Centre Vulnerability Reduction
(WMC) UNDP/World Bank/ WHO Special Programme for Research and Training in Tropical Disease
(TDR) ISBN 92 4 159107 2.
230
Book Review
Comprehensive guidelines for prevention and control of
dengue and dengue haemorrhagic fever#
(Revised and expanded edition)
SEARO Technical Publication Series No. 60
Dengue fever (DF) and its severe forms—dengue haemorrhagic fever (DHF) and dengue
shock syndrome (DSS)—have become major international public health concerns. Over the
past three decades, there has been a dramatic global increase in the frequency of dengue
fever (DF), DHF and DSS and their epidemics, with a concomitant increase in disease
incidence (Box 1). Dengue is found in tropical and subtropical regions around the world,
predominantly in urban and semi-urban areas. The disease is caused by a virus belonging
to family Flaviviradae that is spread by Aedes (Stegomyia) mosquitoes. There is no specific
treatment for dengue, but appropriate medical care frequently saves the lives of patients
with the more serious dengue haemorrhagic fever. The most effective way to prevent dengue
virus transmission is to combat the disease-carrying mosquitoes.
According to the World Health Report 1996,[1] the “re-emergence of infectious diseases
is a warning that progress achieved so far towards global security in health and prosperity
may be wasted”. The report further indicated that: “infectious diseases range from those
occurring in tropical areas (such as malaria and DHF, which are most common in developing
countries) to diseases found worldwide (such as hepatitis and sexually transmitted diseases,
including HIV/AIDS) and foodborne illnesses that affect large numbers of people in both the
richer and poorer nations.”
The first confirmed epidemic of DHF was recorded in the Philippines in 1953–1954 and
in Thailand in 1958. Since then, Member countries of the WHO South-East Asia (SEA) and
Western Pacific (WP) regions have reported major dengue outbreaks at regular frequencies.
In India, the first confirmed DHF outbreak occurred in 1963. Other countries of the Region,
namely Indonesia, Maldives, Myanmar and Sri Lanka, have also reported major DHF
outbreaks. These outbreaks prompted a biregional (SEA and WP regions) meeting on dengue
in 1974 in Manila, the Philippines, where technical guidelines for the diagnosis, treatment,
and prevention and control of dengue and DHF were developed. This document was later
revised at a summit meeting in Bangkok in 1980.
In May 1993, the Forty-sixth World Health Assembly (46th WHA, 1993) adopted a
resolution on dengue prevention and control, which urged that the strengthening of national
and local programmes for the prevention and control of dengue fever (DF), DHF and DSS
should be among the foremost health priorities of those WHO Member States where the
#
http://www.searo.who.int/LinkFiles/Dengue_DHF_prevention&control_guidelines_rev.pdf
231
Comprehensive guidelines for prevention and control of dengue and dengue haemorrhagic fever
Box 1: Dengue and dengue haemorrhagic fever: Key facts
•
Some 2.5 billion people – two fifths of the world’s population in tropical and subtropical
countries – are at risk.
•
An estimated 50 million dengue infections occur worldwide annually.
•
An estimated 500 000 people with DHF require hospitalization each year. A very large
proportion (approximately 90%) of them are children aged less than five years, and
about 2.5% of those affected die.
•
Dengue and DHF is endemic in more than 100 countries in the WHO regions of Africa,
the Americas, the Eastern Mediterranean, South-East Asia and the Western Pacific. The
South-East Asia and Western Pacific regions are the most seriously affected.
•
Epidemics of dengue are increasing in frequency. During epidemics, infection rates
among those who have not been previously exposed to the virus are often 40% to 50%
but can also reach 80% to 90%.
•
Seasonal variation is observed.
•
Aedes (Stegomyia) aegypti is the primary epidemic vector.
•
Primarily an urban disease, dengue and DHF are now spreading to rural areas worldwide.
•
Imported cases are common.
•
Co-circulation of multiple serotypes/genotypes is evident.
disease is endemic. The resolution also urged Member States to: (1) develop strategies
to contain the spread and increasing incidence of dengue in a manner sustainable; (2)
improve community health education; (3) encourage health promotion; (4) bolster research;
(5) expand dengue surveillance; (6) provide guidance on vector control; and (7) prioritize
the mobilization of external resources for disease prevention. In response to the World
Health Assembly resolution, a global strategy for the operationalization of vector control was
developed. It comprised five major components, as outlined in Box 2.
Box 2: Salient features of global strategy for control of DF/DHF vectors
•
Selective integrated mosquito control with community and intersectoral participation.
•
Active disease surveillance based on strong health information systems.
•
Emergency preparedness.
•
Capacity-building and training.
•
Intensive research on vector control.
232
Comprehensive guidelines for prevention and control of dengue and dengue haemorrhagic fever
Accordingly, several publications were issued by three regional offices of the World Health
Organization—South-East Asia (SEARO) [Monograph on dengue/dengue haemorrhagic fever in
1993, a regional strategy for the control of DF/DHF in 1995, and Guidelines on Management
of Dengue Epidemics in 1996]; Western Pacific (WPRO) [Guidelines for Dengue Surveillance
and Mosquito Control in 1995]; and the Americas (AMRO PAHO) [Dengue and Dengue
Haemorrhagic Fever in the Americas: Guidelines for Prevention and Control in 1994].
A 2002 World Health Assembly resolution (WHA 55.17) urged greater commitment to
dengue from Member States and WHO. In 2005, the International Health Regulations (IHR)
were formulated. These regulations stipulated that Member States detect and respond to
any disease (for example, dengue) that has demonstrated the ability to cause serious public
health impact and spread rapidly internationally.[2]
More recently, a biregional (SEA and WP regions) Asia-Pacific Dengue Strategic Plan
(2008–2015) was developed to reverse the rising trend of dengue in the Member countries
of these Regions. This has been endorsed by the Regional Committees of both the SouthEast Asia Region [resolution SEA/RC61/R5 (2008)] and the Western Pacific Region [resolution
WPR/RC59/R6 (2008)].
Due to the high disease burden, dengue has become a priority area for several global
organizations other than WHO, including the United Nations Children’s Fund (UNICEF),
United Nations Environment Programme (UNEP), the World Bank, and the WHO Special
Programme for Research and Training in Tropical Diseases (TDR), among others.
In this backdrop, the 1999 Guidelines for Prevention and Control of Dengue/DHF
(WHO Regional Publication, SEARO No. 29) have been revised, updated and rechristened
as the “Comprehensive Guidelines for Prevention and Control of Dengue and Dengue
Haemmorhagic Fever: Revised and Expanded”. These Guidelines incorporate new
developments and strategies in dengue prevention and control.
References
[1] World Health Organization. The World Health Report 1996: fighting disease, fostering development.
Geneva: WHO, 1996. p. 137.
[2] World Health Organization. International Health Regulations. 2005. 2nd edn. Geneva: WHO, 2008.
233
Book Review
Progress and prospects for the use of genetically
modified mosquitoes to inhibit disease transmission#
Report on planning meeting 1
Technical consultation on current status and planning for future development of
genetically modified mosquitoes for malaria and dengue control
World Health Organization, Geneva, Switzerland, 4-6 May 2009
The use of genetically modified mosquitoes (GMMs) for disease control has social, economic
and ethical implications, so it is important that the World Health Organization (WHO) and its
partners provide guidance to countries on these issues. In collaboration with the Foundation
for the National Institutes of Health (FNIH), TDR has developed a series of planning meetings
on Progress and prospects for the use of genetically modified mosquitoes to inhibit disease
transmission. These technical and public consultations will focus on current status and
planning for future development.
The first technical consultation on genetically modified mosquitoes for malaria and
dengue control was held at WHO headquarters in Geneva, Switzerland in May 2009. The
meeting was attended by 38 scientists and specialists from 13 countries. Its main objectives
were to update participants about progress made; to identify issues, challenges and needs; and
to make recommendations on how to develop internationally acceptable guidance principles
for GMM testing. Discussions focused on the requirements for safety and efficacy testing for
human health and the environment, on selection of locations and conditions appropriate for
field testing (including regulatory requirements and community engagement) and on needs
for communication with end-users and stakeholders. This report summarizes the issues
covered and outlines the meeting outcomes. It highlights progress made and recommends
how to address the issues, challenges and needs identified during the meeting.
GMM approaches under active investigation for control of malaria and dengue
transmission were reviewed. These include : 1) population suppression, defined as reducing
numbers of diseasetransmitting mosquitoes without affecting the transmission capability of
remaining individuals (e.g. through individual sterility); and 2) use of transmission-inhibited
populations, in which Aedes and Anopheles populations have a high proportion that are
unable to transmit malaria-causing or dengue-causing pathogens because of population gene
replacement. Much progress has been made in recent years, and several of these strategies
have achieved proof-of-principle in laboratory studies. A GMM version of the sterile insect
technique (SIT) for Aedes aegypti is moving to caged field trials, and a GMM version of
SIT for Anopheles gambiae may progress to caged field trials in coming years. Other GMM
#
http://apps.who.int/tdr/publications/training-guideline-publications/gmm-report/pdf/gmm-report.pdf
234
Progress and prospects for the use of genetically modified mosquitoes to inhibit disease transmission
strategies, including self-sustaining technologies to achieve long-term transmission control,
are anticipated to advance to field testing in the near future.
To update participants on alternative (non-GMM) approaches, speakers involved in
developing such technologies were invited to review the progress of two biocontrol methods.
Classical radiation-induced SIT for Anopheles arabiensis is expected to enter open field trials
soon, and Wolbachiamediated biocontrol of Aedes aegypti is already undergoing caged field
testing. Approaches to testing and evaluation of these alternative non-GMM technologies may
help efforts to develop GMM technologies, since they share common aspects with regard to
rearing and releasing mosquitoes as well as with regard to monitoring efficacy.
While various GMM development approaches share some issues, they also present
different challenges specific to individual products and applications. This consultation
addressed practical and technical issues related to the testing of GMM technologies. Although
aspects of GMM development and deployment may be governed by established national
and international guidelines, regulations and laws regarding recombinant DNA, biological
safety, biocontrol and/or pesticides, some features of the envisioned technologies fall outside
of existing regulatory schemes. Thus, guidance principles for safety and efficacy testing are
needed urgently for when GMM products move from the laboratory to the field.
The main recommendation of the technical consultation meeting was that a working
group be charged to produce a guidance framework for the evaluation of GMM for malaria
and dengue control. Based on existing literature, regulations and experience, the working
group will propose quality standards for assessing safety and efficacy. It will also address
ethical, legal, social and cultural issues during the design, conduct, recording and reporting
of all phases of GMM field trials prior to deployment. The guidance framework is intended
to foster standardization of procedures, comparability of results and credibility of conclusions
with regard to independent testing (without conflicts of interest) of various GMM strategies.
Compliance with the principles proposed in the GMM guidance framework document
should assure that technical and ethical standards have been adhered to within trials, and
thus facilitate countries’ decisionmaking regarding GMM as a public health tool for malaria
and dengue control.
Included in the main recommendation of the meeting is the development of a
communication plan that promotes transparency of the processes used to produce,
regulate and use GMM. As part of this plan, an open review activity should be designed
and implemented to make the deliberations and decisions of the working group available
for comment by scientists, officials, non-governmental organizations, the media and other
interested persons and agencies.
A guidance framework working group has been established and it is anticipated that it
will complete its activities within the next year and that a public consultation meeting would
be organized thereafter.
235
Book Review
Action against dengue:
Dengue Day campaigns across Asia#
Dengue continues to pose a threat to public health in the South-East Region and the Western
Pacific regions. This threat has been recognized by countries of both the regions, which have
taken action to protect their populations. National leaders also have acknowledged that they
must act regionally in order to protect people within their own borders.
The Association of Southeast Asian Nations (ASEAN) and the World Health Organization
have formed an effective alliance to achieve a shared goal: a healthy and secure
population.
One clear sign of this cooperation was seen on 15 June 2011. ASEAN Health Ministers
declared that day—and each subsequent 15 June—to be ASEAN Dengue Day. This important
annual event allows ASEAN members, in coordination with WHO, to consolidate dengue
prevention and control measures.
ASEAN Member States ought to be congratulated for marking the successful launch of
ASEAN Dengue Day and for affirming the regional partnership needed to address dengue.
This book highlights some of the national and regional events that took place on 15 June
2011 to mark the launching of the first ASEAN Dengue Day.
http://www.wpro.who.int/NR/rdonlyres/50BA9A9C-9297-4A87-9717-2B0148CB45FE/0/ActionAgainstDengueFORUPLOAD.pdf
#
236
Book Review
Crimean-Congo haemorrhagic fever (CCHF) and
dengue fever, Pakistan
Weekly epidemiological record#
No. 44, 2010, 85, 437–444
As of 15 October 2010, 26 cases of Crimean-Congo haemorrhagic fever (CCHF), including 3
deaths, had been notified by the national focal point for the International Health Regulations,
Ministry of Health (MoH), Pakistan. In addition, Pakistan had reported >1500 laboratoryconfirmed cases of dengue fever, including 15 deaths.
Both CCHF and dengue fever are endemic in Pakistan with a seasonal rise in numbers
of cases. However, recently the transmission of both CCHF and dengue fever has intensified
in the country with increased incidence and geographic expansion. The recent Pakistan
floods may have contributed to this upsurge as a result of changes in risk factors for these
diseases.
Operational response
The MoH has scaled up response activities to prevent and mitigate CCHF and dengue fever,
including awareness-raising campaigns on exposure risks and preventive measures for the
general public, strengthening clinical and case management of patients with haemorrhagic
fevers, stockpiling appropriate drugs and personal protective equipment, and implementing
targeted vector control activities.
At the request of the MoH of Pakistan, WHO is mobilizing experts in the clinical
management of severe dengue fever and in infection control in health-care settings through
the Global Outbreak Alert and Response Network (GOARN). WHO is also assisting the
country with resource mobilization, strengthening disease surveillance, laboratory diagnostics,
and training of healthcare providers.
Further information can be found at http://www.who.int/csr/disease/dengue/en/index.
html and http://www.who.int/csr/disease/crimean_congoHF/en/index.html
#
http://www.who.int/wer
237
Instructions for contributors
Dengue Bulletin welcomes all original research
papers, short notes, review articles, letters to
the Editor and book reviews which have a
direct or indirect bearing on dengue fever/
dengue haemorrhagic fever prevention and
control, including case management. Papers
should not contain any political statement or
reference.
Manuscripts should be typewritten in
English in double space on one side of white
A4-size paper, with a margin of at least one
inch on either side of the text and should
not exceed 15 pages. The title should be as
short as possible. The name of the author(s)
should appear after the title, followed by the
name of the institution and complete address.
The e-mail address of the corresponding
author should also be included and indicated
accordingly.
References to published works should
be listed on a separate page at the end of the
paper. References to periodicals should include
the following elements: name and initials of
author(s); title of paper or book in its original
language; complete name of the journal,
publishing house or institution concerned; and
volume and issue number, relevant pages and
date of publication, and place of publication
(city and country). References should appear
in the text in the same numerical order (Arabic
numbers in parenthesis) as at the end of the
article. For example:
(1) Nimmannitaya S. Clinical spectrum
and management of dengue
haemorrhagic fever. The Proceedings
of the International Conference
on Dengue Haemorrhagic Fever,
Kuala Lumpur, September 1-3,
1983:16-26.
238
(2) Gubler DJ. Dengue and dengue
haemorrhagic fever: Its history and
resurgence as a global public health
problem. In: Gubler DJ, Kuno G (ed.),
Dengue and dengue haemorrhagic
fever. CAB International, New York,
NY, 1997, 1-22.
(3) Nguyen Trong Lan, Nguyen Thanh
Hung, Do Quang Ha, Bui Thi Mai
Phuong, Le Bich Lien, Luong Anh
Tuan, Vu Thi Que Huong, Lu Thi
Minh Hieu, Tieu Ngoc Tran, Le
Thi Cam and Nguyen Anh Tuan.
Treatment of dengue haemorrhagic
fever at Children’s Hospital N.1, Ho
Chi Minh City, 1991-1996. Dengue
Bulletin. 1997; 22: 150-161.
Figures and tables (Arabic numerals),
with appropriate captions and titles, should
be included on separate pages, numbered
consecutively, and included at the end of
the text with instructions as to where they
belong. Abbreviations should be avoided
or explained at the first mention. Graphs or
figures should be clearly drawn and properly
labelled, preferably using MS Excel, and all
data clearly identified.
Articles should include a self-explanatory
abstract at the beginning of the paper of not
more than 300 words explaining the need/
gap in knowledge and stating very briefly
the area and period of study. The outcome
of the research should be complete, concise
and focused, conveying the conclusions in
totality. Appropriate keywords and a running
title should also be provided.
Articles submitted for publication should
be accompanied by a statement that they have
not already been published, and, if accepted
Instructions for contributors
for publication in the Bulletin, will not be
submitted for publication elsewhere without
the agreement of WHO, and that the right of
republication in any form is reserved by the
WHO Regional Offices for South-East Asia
(SEARO) and the Western Pacific (WPRO).
One hard copy of the manuscript with
original and clear figures/tables and a computer
diskette/CD-ROM indicating the name of the
software should be submitted to:
The Editor
Dengue Bulletin
WHO Regional Office for South-East Asia
Indraprastha Estate
Mahatma Gandhi Road
New Delhi 110002, India
Telephone: 91-11-23370804
Fax: 91-11-23379507, 23370972
Manuscripts received for publication are
subjected to in-house review by professional
experts and are peer-reviewed by experts in
the respective disciplines. Papers are accepted
on the understanding that they are subject to
editorial revision, including, where necessary,
condensation of the text and omission of
tabular and illustrative material.
Original copies of articles submitted for
publication will not be returned. The principal
author will receive 10 reprints of the article
published in the Bulletin. A pdf file can be
supplied on request.
239
ISSN 0250-8362
The WHO Regional Office for South-East Asia, in collaboration with the Western
Pacific Region, has been jointly publishing the annual Dengue Bulletin.
Dengue Bulletin
The objective of the Bulletin is to disseminate updated information on the current
status of DF/DHF infection, changing epidemiological patterns, new attempted
control strategies, clinical management, information about circulating DENV strains
and all other related aspects. The Bulletin also accepts review articles, short notes,
book reviews and letters to the editor on DF/DHF-related subjects. Proceedings of
national/international meetings for information of research workers and programme
managers are also published.
All manuscripts received for publication are subjected to in-house review by
professional experts and are peer-reviewed by international experts in the
respective disciplines.
Dengue
Bulletin
I S S N 0250- 8362

Dengue Bulletin.indb - World Health Organization

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