Module 4: Epidemiology Investigation

Transcription

Module 4:
Epidemiology Investigation
Epidemiology Division
Analysis and Reporting Branch
Bureau of Clinical Laboratories
Bureau of Environmental Services
Module Learning Objectives
Develop a case definition
Explain an epidemic curve
Develop an initial hypothesis
List three types of study design and a
method of statistical analysis
Calculate measures of association
Interpret significance of data
Determine if hypotheses are confirmed or
rejected
Perform group exercise
2
Estimated Annual US
Foodborne Disease Burden
Foodborne Illnesses
47.8 million
Hospitalizations
127 839
127,839
Deaths
3 037
3,037
3
AL Foodborne Outbreak (FBO) Team
Montgomery
Surveillance Branch - Epidemiology
Analysis and Reporting Branch - Epidemiology
Bureau of Clinical Laboratories (BCL)
Bureau of Environmental Services – Food,
Milk and Lodging
Th
Throughout
h
the
h S
State
Environmentalists
Field Surveillance
S r eillance Staff (FSS)
Others (in special situations)
4
5
6
AL Foodborne Outbreak
(FBO) Definition
An incident in which two or more persons from
different households experience a similar illness
resulting from the ingestion of a common food.
Exceptions: botulism and chemical poisoning
(1 case = outbreak)
7
How Are Outbreaks Named?
The outbreak name identifies the state, the year, month,
species/serotype, primary county, and sequence (order
of outbreaks in the same county in the same month).
The format is Alabama/year/month/species, serotype, or
enzyme
y
pattern/hyphen/county
p
yp
y number/ and sequence.
q
PHA03 Deli :
PHA08 Church Luncheon :
26
8
AL Foodborne Outbreaks
9
10
County Numbers
Autauga
Baldwin
Barbour
Bibb
Blount
Bullock
Butler
Calhoun
Chambers
Cherokee
Chilton
Ch t
Choctaw
Clarke
Clay
Cleburne
Coffee
Colbert
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
Conecuh
Coosa
Covington
Crenshaw
Cullman
Dale
Dallas
DeKalb
Elmore
Escambia
Etowah
F tt
Fayette
Franklin
Geneva
Greene
Hale
Henry
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
Houston
Jackson
Jefferson
Lamar
Lauderdale
Lawrence
Lee
Limestone
Lowndes
Macon
Madison
M
Marengo
Marion
Marshall
Mobile
Monroe
Montgomery
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Morgan
Perry
Pickens
Pike
Randolph
Russell
St. Clair
Shelby
Sumter
Talladega
Tallapoosa
T
Tuscaloosa
l
Walker
Washington
Wilcox
Winston
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
11
Develop Initial Case Definition:
C
Counting
i Apples
A l and
dO
Oranges
Sett off criteria
S
it i for
f deciding
d idi whether
h th an
individual should be classified as “ill”
Objective criteria
O
Outbreak-associated vs. normal
background
Value of routine surveillance data
Primary vs. secondary cases
12
Outbreak Case Definitions
Begin general, but become
increasingly specific as information is
gathered
Person, Place and Time association
Clinical criteria
Classify cases based on certainty
Confirmed ((positive lab))
Probable (no lab; symptoms)
Suspect (no lab; some symptoms)
13
Revise Case Definitions
Ongoing throughout investigation
P i d
Precise
definitions
fi i i
reduce
d
potential for misclassification:
Estimated 36% of enteric infections
are foodborne;
I
Incomplete
l t case history
hi t
can haunt
h
t you;
Incorrectly classifying individuals can bias results;
Make it harder to detect true associations.
associations
14
Misclassification Example:
S l dE
Salad
Exposure
Not ill
Salad Yes (?)
Not ill
Salad No (?)
15
Exposure Date Incubation Period
Norovirus average incubation period: 36 hrs (range: 10-50 hrs)
16
Exposure Date Incubation Period
3 6 9 12 15 21 24 27 30 33 36 39 42 45 48 51 54
Norovirus average incubation period: 36 hrs (range: 10-50 hrs)
17
Make Epidemiologic Associations
Person, Place,
P
Pl
Ti
Time
Systematically
y
y organize
g
key
y
information
Develop initial hypothesis
18
Person: AL Outbreak Examples
p
19
Symptoms:
y p
Frequency
q
y Table
20
Place: Common
Exposure Location
Case 1 – rest. A, B, C, D
Case 2 – rest. B, E, F
Case 3 – rest. A, B, G, H, I
Case 4 – rest. B,, D,, J,, K
What is the common exposure location?
21
Place: Common
E
Exposure
Location
L
ti (cont.)
(
t)
Restaurant
Same restaurant
Multiple
p restaurants,, same chain or
owner
Multiple
p chains, common distributor
Banquets, Birthday Parties, Wedding
Receptions, Conferences, Basketball
Game, School Field Trip, Summer
Camp, etc.
22
Place
23
An Epidemic Curve
Nu
umber of C
Cases
Shows progression of outbreak over time
12
11
10
9
8
7
6
5
4
3
2
1
0
X axis = units of time (1/4 to 1/3 of incubation time)
Y axis = number of cases
Fatal
Non-fatal
There is an inherent
delay between the date
off illness onset and the
date the case is
reported to Public
Health
6/27
8/2
9/6
10/11
11/15
Date
12/20
1/24
2/27
4/3
Source: Centers for Disease Control and Prevention
24
Salmonella Outbreak Investigations:
Ti li ffor R
Timeline
Reporting
ti g C
Cases
Patient Eats
Contaminated
Food
1-3 Days Incubation
Time to contact with health
care system = 1-5 days
Stool Sample
Collected
Time to diagnosis = 1-3 days
Shipping Time = 0
0-7
7 days
Public Health
Lab Receives
Sample
Patient
Becomes Ill
Serotyping and “DNA
fingerprinting” Time = 2-10 days
Salmonella
S
Identified
Case
Confirmed
As Part of
Outbreak
Source: CDC
25
Point--Source Exposure
Point
Num
mber of Cases
10
9
8
7
6
5
4
3
2
1
0
1
3
5
7
9
Days
11
13
15
26
Num
mber of Cases
Ongoing Exposure
10
9
8
7
6
5
4
3
2
1
0
1
3
5
7
9
y
Days
11
13
15
27
Num
mber of C
Cases
Secondary Exposures
10
9
8
7
6
5
4
3
2
1
0
1
3
5
7
9
Days
11
13
15
28
Hypothesis
“An unproved theory ...tentatively
accepted to explain certain facts or to
provide a basis for further investigation”
Source: Webster’s New World
Dictionary 3rd Edition
Dictionary,
29
Hypotheses
H th
and
d Questionnaires
Q
ti
i
Hypothesis generating
Hypothesis testing
30
Example of Hypothesis
Food item consumed at the Smith
Wedding reception caused illnesses
Data needed to test information
What kind of food items were eaten?
Who ate the food item? Who did not eat?
How much did each person eat?
Illness onset ((date and time)?
)
31
Develop
p Initial Hypothesis
yp
Multiple
p hypotheses
yp
may
y be
compatible with data initially
Helps clarify
What is known
What is missing
Actions needed to gather
missing information
32
Unknown Causative Agent
g
Review what is known about cases
Symptoms, severity of disease
Events attended or anything
y
g unusual
Foods consumed and methods
p p
of food preparation
Identify most likely agent(s)
Review references
Consultation
33
34
Known Causative Agent
Review what is known about the agent
Typical signs and symptoms
Modes of transmission
Foods in past outbreaks
Is this situation similar to other
previously reported incidents?
Be aware of recent food recalls
35
New Routes of Transmission
are Being Identified
Example:
p
E. coli O157:H7 in apple cider
36
Case Definition vs. Hypothesis
Case Definition
Classify cases
vs. controls
Includes
Person
Place
Time
Symptoms
Hypothesis
Describe
exposure to
test analytically
Theory
Do NOT include
hypothesis in case
definition!
37
Group Exercise
Case Definition and Hypothesis
38
Questionnaire Design/
Interview Process
Questions should be clear
clear, concise and
asked in an uniform way
Avoid open
open-ended
ended questions
questions, unless
hypotheses generating questionnaire
Include menu, when available, to avoid
recall bias
Questionnaire should take into account
Q
completeness of data collection, time
involved, and relevance of questions
39
Questionnaire Design/
Q
g /
Interview Process -2
Include as many not-ill as possible;
Review questionnaire to make sure
there is no conflicting/missing
information to avoid calling back;
Stool and food samples are very
helpful in solving the outbreak
40
Examples of
Epidemiological Studies
1. Case Series
2. Cohort Studies
3. Case-Control Studies
41
1.
1 Case Series
A
Appropriate
i t to
t use if:
if
Small number of cases (< 5)
Controls are unavailable (e
(e.g.,
g
everyone ill)
Provide person
person, place
place, and time
associations
42
2.
2 Cohort Studies
Groups of exposed and unexposed
individuals can be easilyy identified
Compare risk of illness by what
was/was not eaten
Example: Church supper
43
3.
3 CaseCase-Control Studies
Typically used in foodborne
investigations when:
Exposed group is very large or
Exposed group is not easily identified
Compare ill with non-ill
Individuals to determine likelihood of
having eaten specific foods
Examples:
E
l
very llarge wedding
ddi reception
ti
or sporadic E. coli cases
44
Measures (Calculations)
Measure of Occurrence
Attack Rate
Measure of Association
Relative Risk (RR): Cohort studies
Odds Ratio (OR): Case-Control
Case Control studies
45
Attack Rate: Measure of Occurrence
Attack Rate (AR)
Expresses occurrence of a disease
among a particular at-risk population for a
limited period of time
time, often due to a very
specific exposure.
Can be event
event-specific
specific or food
food-specific
specific
Number ill people who consumed item
AR =
Total number people consuming item
46
Measures of Association Between
Exposure (Food Item) and Disease
Depends on type of study
“Relative risk”  cohort studies
Risk of developing disease given the
exposure
“Odds ratio”  case-control studies
Odds off having
Odd
h i the
th exposure given
i
th
the
disease
Computer programs greatly speed
the calculations
47
Estimatingg Risks Associated
with “Exposure”
Compare attack rates among
exposed and unexposed
Relative Risk =
Attack Rate (exposed) / Attack Rate (unexposed)
48
2 by 2 Table to Calculate
Relative Risk
Estimates magnitude of association between exposure and
p
group
g
p relative to unexposed
p
group
g
p
disease in exposed
Disease
Yes ( + )
Yes ( + )
No ( - )
total
a
b
a+b
RR =
E
Exposure
No ( - )
c
d
c+d
total
a+c
b+d
a+b+c+d
a / ((a + b))
c / (c + d)
49
Relative Risk - Cohort Studies
Measurement of the risk of
developing disease given a specific
exposure (a food item)
Compares attack rates between
exposed and unexposed groups
g Exposed = a / (a + b)
Relative Risk = Attack Rate ((AR)) among
( + d)
Attack Rate (AR) among Unexposed c / (c
(RR)
50
Number of persons who ate
specified item
Baked ham
Spinach
Mashed potato
Cabbage salad
Jello
Rolls
Brown bread
Milk
Coffee
Water
Cakes
Ice cream ((van))
Ice cream (choc)
Fruit salad
Number of persons who did
not eat specified item
Ill
Not Ill
Total
Attack rate (%)
Ill
Not Ill
Total
Attack rate %
29
26
23
18
16
21
18
2
19
13
27
43
25
4
17
17
14
10
7
16
9
2
12
11
13
11
22
2
46
43
37
28
23
37
27
4
31
24
40
54
47
6
63
60
62
64
70
57
67
50
61
54
67
80
53
67
17
20
23
28
30
25
28
44
27
33
19
3
20
42
12
12
14
19
22
13
20
27
17
18
16
18
7
27
29
32
37
47
52
38
48
71
44
51
35
21
27
69
59
62
62
60
58
66
58
62
61
65
54
14
74
61
Reference: CDC Epi-Ready Training Manual
51
Church Supper Cohort Study –
Relative Risk
V ill iice cream
Vanilla
AR (exposed) ÷ AR (unexposed)
79 6 ÷ 14.3
79.6
14 3 = 5.6
56
Persons consuming vanilla ice cream
were 5.6 times more likelyy to become ill
than those who did not eat vanilla ice
cream
52
Number of persons who ate
specified item
Baked ham
Spinach
Mashed potato
Cabbage salad
Jello
Rolls
Brown bread
Milk
Coffee
Water
Cakes
Ice cream ((van))
Ice cream (choc)
Fruit salad
Number of persons who did
not eat specified item
Ill
Not Ill
Total
Attack rate (%)
Ill
Not Ill
Total
Attack rate %
29
26
23
18
16
21
18
2
19
13
27
43
25
4
17
17
14
10
7
16
9
2
12
11
13
11
22
2
46
43
37
28
23
37
27
4
31
24
40
54
47
6
63
60
62
64
70
57
67
50
61
54
67
80
53
67
17
20
23
28
30
25
28
44
27
33
19
3
20
42
12
12
14
19
22
13
20
27
17
18
16
18
7
27
29
32
37
47
52
38
48
71
44
51
35
21
27
69
59
62
62
60
58
66
58
62
61
65
54
14
74
61
Reference: CDC Epi-Ready Training Manual
53
Church Supper Cohort
Study - Relative Risk
Study
Chocolate ice cream
AR (exposed) ÷ AR (unexposed)
53 2 ÷ 74.1
53.2
74 1 = 0.7
07
Persons consuming chocolate ice
cream were 0.7 times as likely (or
30% less likely) to become ill than
those who did not eat chocolate ice
cream
54
2 by 2 Table to Calculate
Odds Ratio
Estimates magnitude of association between exposure and disease
in diseased group (cases) relative to non-diseased group (control)
Disease
Y (+)
Yes
N (-)
No
t t l
total
Yes ( + )
a
b
a+b
No ( - )
c
d
c+d
total
tota
a+c
b+d
a+b+c+d
Exposure
ad
a/c
OR = b/d =bc
55
Odds Ratio Case--Control Studies
Case
Measurement of the odds of having
an exposure (specific food
consumption) given the disease
Estimates the Relative Risk derived
from cohort studies
56
How Valid are Your Findings?
Is the observed association between exposure
and disease (expressed by the RR or OR) due to
alternative explanations?
Bias: systematic error
Selection
Information ((recall, interviewer,
misclassification)
Chance
Sampling variability
Sampling size
57
Examples of Bias
Random misclassification of cases vs.
controls or exposed vs. unexposed
biases OR or RR toward “1”
Recall bias
cases remember exposures
p
better than do
controls
problem with retrospective studies
may result in inflated OR
58
Evaluatingg the Role of Chance
P-value
Probability
P
b bilit a given
i
association
i ti could
ld h
have
occurred by chance alone
“Statistically significant” defined as p ≤ 0.05
Consider all available evidence when
interpreting p-values
95% Confidence Interval
Range within which the true association lies,
based on 95% assurance
59
P-values and Confidence Intervals
Example 1
Table 16
Analysis of Food Item 2
ILL
ITEM2
|
+
- | Total
-----------+---------------+-----+ |
5
10 |
15
- |
9
11 |
20
-----------+---------------+-----Total |
14
21 |
35
5 / (5 + 10) .3333
RR = 9 / (9 + 11) = .45
• RR= 0.74
• 95% confidence limits for RR =
0.43 < RR < 2.79 Not significant because includes “1”
•P-value = 0.486
Not significant because
more than “0.05”
60
Example 2
Table 15
Analysis of Food Item 1
ILL
ITEM1
|
+
- | Total
-----------+---------------+-----+ |
11
4 |
15
- |
3
17 |
20
-----------+---------------+-----Total |
14
21 |
35
11 / (11 + 4) .7333
RR = 3 / (3 + 17) = .15
• RR= 4.89
• 95% confidence limits for RR =
1.65 < RR < 14.50 Significant because does not include “1”
•P-value = 0.000490
Significant because
less than “0.05”
61
Example 2 (cont.)
Indicates that best estimate of increased risk of
illness associated with consumption of food item 1 is
4.89 times;
We are 95% confident that the true risk ratio is no
less than 1.65 and no greater than 14.5 times the risk
of those not consuming this item. Lack of inclusion
of 1.0 in this interval demonstrates a significantly
positive association.
62
Increase the Sample Size
Increase the number of controls (persons not ill)
Outbreak
☺
Controls
# Ill
# Not Ill
12
3
14
7
11
11
7
21
Cases
63
Provide Denominator
Among Exposed
Example: AL1003JEG-26a
G
(C
(Church)
)
15 Interviewed (11 ill, 4 not ill)
2 events (Banquet on Saturday
and Luncheon on Sunday)
60-65 attended banquet
q
20-25 attended luncheon
64
P-value: Effect of Sample Size
Disease
Exposure
Ill
+
Not ill
-
Total
Eat food +
4
1
5
Did not eat food -
1
2
3
5
3
8
65
P-value: Effect of Sample Size (cont.)
Disease
Exposure
ill
+
Not ill
-
Total
Ate food +
8
2
10
Did not eat food -
2
4
6
10
6
16
66
P-value: Effect of Sample Size (cont.)
Disease
Exposure
Ill
+
Not ill
-
Total
Ate food +
12
3
15
3
6
9
15
9
24
Did not eat food -
67
True Story
4 friends meet for dinner
3 eat chicken fried rice
1 chop suey
3 ill with vomiting
g & diarrhea 1218 hrs. after meal
No samples
p
available for testing
g
Time temperature abuse of fried
rice documented
P-value = 0.2
Is this a foodborne outbreak?
68
The Significance of Significance
“Not significant” doesn’t necessarily mean “no
association ”
association.
The measure of association (relative risk, odds
ratio)) indicates the direction and strength
g of the
association.
The statistical test (p-value), indicates how likely it
is that the observed association may have occurred
by chance alone.
No significance
g
may
y reflect no association in the
source population but may also reflect a study size
too small to detect a true association in the source
population
population.
Source: Field Epidemiology, 1996, Michael B. Gregg
69
Interpret Results
Hypotheses confirmed or rejected?
If rejected, develop new hypotheses
Test new hypotheses
y
by:
y
More analysis with existing data
Gather and analyze new data
Final conclusions
Was it foodborne?
70
Problems Can Interfere
with Outbreak Solution
Questionnaire design
Data collection ((ex., incomplete data))
Sample size (ill and not ill)
No clinical or food sample for testing
Reporting time
71
Statistical Summary
RR is calculated in cohort studies
RR compares rate of illness in exposed group to rate
of illness in unexposed group
OR is calculated in case-control studies
OR = odds in favor of exposure among cases
compared to the odds in favor of exposure among
the controls
RR and OR are both measures of association
“Not significant” ≠ “No association”
No significance may reflect lack of association but
may also reflect a study size too small to detect true
association
72
Statistical Take Home Message
g
If RR or OR = 1, then there is no association
between consuming food item and getting sick;
If RR or OR is less than 1, then food item is
“protective”;
If RR or OR is more than 1, then food item is
“implicated”;
If the 95% CI includes 1
1, then the result is not
considered statistically significant (i.e. there is no
statistical difference between the groups);
The lower the p-value the more unlikely the results
are due to chance
73
Multi--state FBOs
Multi
Not all agents are created equal (e.g. S. typhimurium)
Microbes have fingerprints
g p
too!
CDC monitors a database (PulseNet) with microbial
fingerprint information and notifies states that are part
off multi-state outbreaks;
Periodical conference calls with involved states and
regulatory agencies to collaborate on outbreak
investigation and response;
More information from cases may be needed
CDC and ADPH website, links, and media coverage
74
75
National 2010 FBOs
76
Module Summary
T k Home
Take
H
Points
P i t
Have a working Case Definition and Hypothesis;
B aware off possible
Be
ibl routes
t off ttransmission
i i ((new
and old);
Questionnaire design is paramount;
Interview as many people as possible including
“not ill”;
Avoid misclassification (exposure) and bias (e. g.
recall, selection); Timeliness of reporting is key;
Communication is extremely important;
Outbreak investigation is a collaborative effort!
77
Module Learning Objectives
Developed a case definition
Explained an epidemic curve
Developed an initial hypothesis
Li t d th
Listed
three ttypes off study
t d design
d i and
da
method of statistical analysis
Calculated measures of association
Interpreted significance of data
D t
Determined
i d if h
hypotheses
th
are confirmed
fi
d or
rejected
78
Group Exercise
Joe’s Thanksgiving Dinner Outbreak
79

Module 4: Epidemiology Investigation

Transcription

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