socio-demographic determinants of malaria in highly infected rural

SOCIO-DEMOGRAPHIC DETERMINANTS OF
MALARIA IN HIGHLY INFECTED RURAL
AREAS: REGIONAL INFLUENTIAL
ASSESSMENT USING GIS
Prashanthi Devi, M., Ranganathan, C R and
Balasubramanian, S
Division of RS and GIS
Department of Environmental Sciences
Bharathiar University,
Coimbatore – 641 046
India
INTRODUCTION
• Natural ecosystems throughout the
world have been severely altered by the
human intervention .
• The rapid urbanization in many parts of
the world is changing the context for
human population and the natural
ecosystem interaction ….
• Resulting in occurrence of diseases
MALARIA
To understand the complex nature of the mosquito human
relationship, it is required to identify the type of
• human migration,
• population growth,
• socio economic status,
• behavior and
• the environmental aspects around them.
This underscores the importance of
• how humans modify the environment to affect the
mosquito vector population and
• the intensity parasitic transmission in the endemic
areas, be it rural or urban areas.
To understand the influence of human activity on malaria
vector population dynamics is very important
• So as to identify the areas in need for the source
reduction efforts and further control
• The key determinants of the outcome of malaria have been
related to human host, the parasite, vector or the
environmental parameters
• Vector densities have been normally higher in rural areas
due to favourable habitats than in urban areas
Poverty
Farming activities
Deteriorating infrastructure
Over crowding
Less protection in the house holds
The potential factors could be identified based on
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the type of house construction
the socio economic status of the public
livestock dependence
behavioral aspects among the residents
drainage
the distance to streams
the infectious-bite avoidance pattern
Objectives
• to record the socio economic and the demographic data
in highly endemic zones of the Salem district
• using a Questionnaire and
• a hand held GPS (Garmin III Plus).
• As all the data were collected with house
hold identifiers, opportunities for
examining the spatial hypothesis exist.
• The map of study of households and the
related surveyed region can be linked to
the existing data sources through GIS.
Status of Malaria in Salem
à The Directorate of Health under the Government of
Tamil Nadu - 74 Primary Health Centers (PHC) in the
district in both rural and urban areas.
à As the climatic condition favours the survival of
mosquitoes this region had been demarked as one the
highly endemic zones in the state.
à The major species identified are Anopheles and Culex
sps.
Malaria in Salem
à The present selected region has been marked has an
highly endemic PHC region with at least a minimum of 5
cases reported every month.
à Outbreaks of epidemics in this area, in 1996 and 2004,
prove that the habitat of the vector has increased.
à After the outbreak, this region has been taken under
close examination.
Survey
• The hamlets that could be visited by either walk or by
tractors were only chosen for the study.
• Each household data was collected based on the house
number and the questionnaire was filled in by personal
interview with the people.
• The living habitats of the people, occupational pattern and
basic village amenities were also enquired about.
• The distance to the village hospital from the hamlet was also
measured
• The survey was carried out during the month of October
2004 at four infected villages that come under the Vellar
PHC and one non-infected village under the
Santhaithanapatty PHC.
• Random sampling was done in each village for 206
samples which were geocoded using Garmin III Plus
GPS
• The surveyed information was recorded into a database
using EpiInfo where a questionnaire is prepared as a
sheet.
• The data were later imported into the Arcview GIS 3.2a
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The slope of the study area was
calculated by the generation of a
Digital Elevated Model (DEM) using
Arcview
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The NDVI of these villages
calculated using ERDAS Imagine 8.5
image processing software for the
subsequent month of Nov 2004
Disease determinants
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Presence of mosquitoes
Vegetation (NDVI)
Slope (DEM)
Drainage facility
Wood storage
Sanitation
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Livestock Dependance
Waterbody
Education
House type (Reinforced concrete, Tiled,
Thatched, Combined)
Source of water
Prevention measures or avoidance behavior
logit y = β0 + β1(X1) + β2(X2) + β3(X3) + β4(X4) + β5(X5)+ β6(X6)+
βa(Xa)+ βb(Xb) + βc(Xc)+ βc(X10) +βc(X11)
SIGNIFICANCE
Infected Areas
• The proximity to water body
• House type
• The avoidance behavior
Controlled Areas
• Insignificant
FINDINGS
• As the main occupation of the people is farming, the economic
status is low and even below poverty level
• The people were found live closer to their farms and hence
stagnation of water in the fields and also the stagnation caused
due to improper drainage had lead to breeding of the mosquitoes.
• The houses had mostly thatched roofs. Even in case of house
type being reinforced concrete, the adjacent cattle barns were
made of thatched roofs, which provide a suitable place to
mosquito breeding.
• The usage of open ground tanks for water storage is the another
main breeding site.
• Awareness of proper sanitation facilities and avoidance behavior
also has added to the context.
• The people stayed outside their houses most of the days i.e.,
the people slept outside their houses in the evenings or
nights when the mosquito activity is at its peak
• Clothing habits referred to partial or improper clothing to
facilitate the daytime heat.
• Mostly people reared cattle and other livestock within their
house premises which led to constant favorable moisture for
mosquito proliferation.
• In the infected areas, the schools were situated closer to the
farms or had water storage tanks near them. This led to the
children being infected more than the elders.
CONCLUSIONS
• Identify target variables that potentially favour the mosquito
breeding sites in the survey area
• In behaviourly focusing social mobilization and
communication programs that may be implemented to
reduce the breeding sites based on community involvement
• Resource allocation can be recommended to such areas and
also other infected areas based on population-basedsurveys, which can be conducted as a component of malaria
control surveillance.
THANK YOU