Epidemic investigation

1. Investigating An Outbreak
Dr Amita Kashyap
Sr. Prof. P.S.M.
S.M.S.Medical College, Jaipur
1

2. Immunity and Susceptibility
• The amount of disease in a population depends
on a balance between the number of susceptible
people in that population and the number of
people who immune, and therefore not at risk.
• people may be immune because they have had
the disease previously or because they have been
immunized OR on a genetic basis.
• When balance moves toward susceptibility, the
likelihood of an outbreak increases.

3. Herd Immunity
• If a large percentage of the population is
immune, the entire population is likely to be
protected, not just those who are immune.
• For herd immunity to exist :-
– The disease agent must be restricted to a single host
species within which transmission occurs,
– Transmission must be relatively direct from one
member of the host species to another.
– No other means of transmission are available.
– Infections must induce solid immunity.
– If the probability of an infected person encountering
every other individual in the population (random
mixing) is the same

4. Effect of herd immunity, United States, 1958–1961

5. Incubation Period
• The incubation period is defined as the interval
from receipt of infection to the time of onset of
clinical illness.
• Different diseases have different incubation
periods. A precise incubation period does not
exist for a given disease; rather, a range of
incubation periods is characteristic for that
disease.
• In general, the length of the incubation period is
characteristic of the infective organism

6. Incubation periods of viral diseases

7. Incubation periods for 191 delegates affected by
a Salmonella typhimurium outbreak

8. Number of cases plotted against time and
against the logarithm of time

9. What is a Disease Outbreak?
Outbreak vs Epidemic
What does it Require?
A pathogen in sufficient quantities,
A mode of transmission,
And a pool of susceptible people
9

10. 10
A Scenario!
A 23 yr old male student; presented at 10:30 pm
on 17th Jan 2014, at the emergency complaining
of a sudden onset of abdominal cramping,
nausea and diarrhea. He was weak, not severely
distressed, had no fever or vomiting.
A No. of other students, all with the same
symptoms, visited emergency over next 20 Hrs
All treated with Fluid replacement recovered
fully within 24 hrs. of the onset of illness.

11. Does it warrant an
investigation?
• Why?
11

12. When should we Investigate?
• Number and severity of persons
affected!
• Uncertainty about cause!
• Level of Public Concern/ Political
pressure!!
• Potential for contributing to medical
knowledge!
12

13. 13
Reasons for Outbreak Investigation
Quantifying the epidemic (Descriptive
epidemiology)
Getting at the source and reasons (Analytic
epidemiology)
for
Preventing others from becoming affected

14. Investigation in our scenario!
Quick information revealed 47 students out of
1164 college enrollment got affected by 8 PM
on 18th Jan (within 20 Hrs)
 What is the quantitative measure of the extent
of an outbreak?
No. of New Cases
AR = Persons at Risk
What is the AR for this period?
= 47/ 1164 X 100 = 4% 15

15. Hostel wise distribution of 47 known cases, AR,
population and sex of the occupants of each hostel
Hostel For Sex PAR No. of
Cases
AR
1 F 80 19 23.8
2 F 62 2 3.2
3 F 89 0 0
4 F 61 1 1.6
5 F 53 5 9.4
6 M 35 0 0
7 M 63 0 0
8 F 103 4 3.9
9 M 35 1 2.9
10 M 37 0 0
11 F 34 1 2.9
12 M 62 13 21.0
13 M 32 1 3.1
14 M 10 0 0
Total - 756 47 6.2
Attack Rate (all students) =
47/ 1164 X 100= 4%
Attack Rate (hostellers) =
47/ 756X100= 6.2%
Attack Rate (hostel 1, 12) =
19+13/ 80+62 = 22.5%
Attack Rate (other hostels) =
15/ 614 = 2.4%
Risk Ratio = AR hostel (1, 12) /
AR (Other hostels) X 100
= 22.5/ 2.4 = 9.4
? Sex difference in AR =

16. Further :
Visit to hostels revealed that not all
students who became ill reported to
emergency!!!!!
Needed unbiased data- hence……..
Seven hostels were randomly selected for
information collection on desired areas! 17

17. Response to the questionnaire survey by hostels
Questionnaire returned
Selected
Hostel
Population Number Percent No. of ill St.
5 53 49 92.5 13
6 35 26 74.3 13
7 63 28 44.4 15
8 103 65 63.1 21
9 35 19 54.3 5
12 62 44 71.0 22
Nurses’ hostel 60 60 100 17
Unidentified - 13 - 4
Total 411 304 74.0 110
18
AR = 110/304 X100 = 36.2%
Note: initial hostel wise AR for Hostel 6, and 12 were 0% and 21%
As per survey data ! - AR (H6) =13/26X100=50% and AR (H12) =22/44X100 = 50%

18. • Approach for data collection! – note that AR
of hostel 6 and 12 were 0% and 21% by
emergency data but by survey data both are
50%.
• Was emergency data useless?
• Is 36.2% the true AR of AGE on campus ?
• Explain factors why AR estimated from
emergency records were low?
• Why more cases from hostel 1 and 12 at
emergency? 19

19. Additional information…..
• No large gathering of students..... hence inquiries were
made about meals eaten on 16th and 17th Jan
• Most students ate at college cafeteria
• How will you zero down to source of infection?
20
St. who ate specific meal St. who did not eat specific meal
Ill Well Total AR(%) Ill Well Total AR(%)
Jan 16
Breakfast 52 100 152 34.2 51 94 145 35.2
Lunch 89 150 239 37.2 20 44 64 31.3
Dinner 87 150 237 36.7 23 44 67 34.3
Jan 17
Breakfast 56 105 161 34.8 42 89 131 32.1
Lunch 106 145 251 42.2 3 49 52 5.8 RR!
Dinner 78 130 208 37.5 31 64 95 32.6
42.2/ 5.8=7.3

20. Can we now calculate IP?
• Having identified the meal at which the
students most probably were exposed to the
causal pathogen and
• Knowing each student’s time of food
consumption and onset of symptoms; we can!!
21
IP(hrs) No. of Students Cumulative No. of St.
8 22 22
9 11 33
10 18 51
11 8 59
12 42 101

21. 0
10
20
30
40
22
8
11
9
18
10
08
11
42
12
Time (hours)
Number
of
cases
0
20
40
60
80
22
8
33
9
51
10
59
11
100
12
Time (hours)
Cumulative
frequency
%
100
Median I P = 10 hrs

22. What next?
A follow up survey to obtain information about
particular foods that 251 students ate at lunch
on Jan 17!
If students were uncertain about whether they
ate or not the meal in question, they were not
included in the analysis of the particular food.
 As a result total of those who ate or did not eat
each specific item did not equal 251 for all items
23

23. Food specific histories of students who ate lunch at the
college cafeteria on Jan 17th
Food/ beverage St. who ate Sp. Food /
Beverage
St. who did not eat Sp. Food /
Beverage
Ill Well Total AR (%) Ill Well Total AR (%)
Fish Curry 16 36 52 30.8 87 103 190 45.8
Lamb Gravy 95 56 151 62.9 7 82 89 7.9
Chicken noodle 12 57 69 17.4 92 80 172 53.5
Dal Fry 58 54 112 51.8 39 69 108 36.1
Fruit salad 32 39 71 45.1 63 82 145 43.4
Cabbage salad 4 5 9 44.4 95 126 221 43.0
Plain vanilla Ice cream 19 29 48 39.6 80 102 182 44.0
Rabri 62 77 139 44.6 39 56 95 41.1
Milk 91 127 218 41.7 12 13 25 48.0
Coffee 10 31 41 24.4 89 103 192 46.4
tea 23 19 42 54.8 78 114 192 40.6
(RR = 8)

24. Further investigation -
• About preparation of Lamb Gravy revealed that it
was cooked on 16th Jan, refrigerated and warmed
on the morning of 17th Jan
• Now, even without Lab investigation we can
speculate the etiologic agent? Cl. perfringens
• Suggesting features:-
– Gastrointestinal symptoms without fever and
vomiting
– Median I P is 10 Hrs (range 8 – 22 hrs)
– Meat Gravy Dish is the most likely food
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25. 27
• This is the most common form of transmission in food-borne
disease, in which a large population is exposed for a short
period of time.
Point Source Transmission

26. 28
• In this case, there are several peaks, and the
incubation period cannot be identified.
Continuing Common Source or
Intermittent Exposure

27. Propagated Outbreaks
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28. Warning Signals of an impending outbreak
• Clustering of cases/ deaths in Time/Place
• Unusual increase in cases/ deaths
• Even a single case of measles , AFP, Cholera, Plague,
Dengue, or JE
• Ac. febrile illness of unknown etiology
• Two or more epidemiologically linked cases of outbreak
potential
• Unusual isolates
• Shifting in age
• High or sudden increase in vector density
• Natural Disaster

29. Unusual
Health Event
No
Yes
Is this an
outbreak
Etiology, Source
& Transmission
known?
No
Yes
Institute control
measures
Further Investigation
Describe outbreak
in terms of TPP
Continued….

30. Develop Hypothesis regarding
Source, Transmission, Etiology & PAR
yes No
Does the
Hypothesis
Fit with facts
Institute control
measures
Special studies
Remember that outbreak is usually
a sudden & unexpected event!
There is need to act quickly.
A systematic Approach Helps

31. Epidemic preparedness
• Formation & Training of RRT
• Regular review of data
• Alertness during known ‘outbreak season’
• Identifying outbreak prone areas
• Ensuring that these areas have necessary drugs and
materials (including transport media)
• Identifying & strengthening the labs
• Designating vehicles
• Ensuring communication channels

32. Steps of Outbreak Investigation
• Verification of the outbreak
• Sending the RRT
• Monitoring the situation
• Response to an outbreak
• Interim report by RRT within one week
• Declaring the outbreak to be over
• Final report & its Review within 10 days of the
outbreak declared to be over

33. Nullification of source
Minimizing transmission Protecting
the host
Response to outbreak

34. Analysis
• Analyze and interpret - within 24 hours
• Identify EWS
• Frequency count by reporting unit helps in identifying
outbreaks or potential outbreaks
• Analysis in terms of person, time and place will be able to
focus the intervention;.
• During an outbreak, analysis of the data identifies the most
appropriate and timely control measures.
• Analysis of routine data provides information for predicting
changes of disease rates over time and enables appropriate
action.
Data compilation/analysis and response should be at
all levels.

35. Feedback
Essential to maintain know-how, moral and
support the peripheral staff.
Monthly Feed back Report should be sent
regularly even when there are no
epidemics
Feed back report should also be provided
on the quality of data submitted to the
district surveillance officer