1 Outbreak Investigation WHO

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SEARO CSR Training on Outbreak Investigation

Outbreak Investigation

Best Practice/MethodsPractical Reference Points


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Outbreak Investigation Best Practices/ MethodsSEARO CSR Training on Outbreak Investigation

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Learning Objectives

At the end of the session, the participants

will be able to:

List down the objectives of outbreak

Describe steps in outbreak investigation

Explain the importance of conducting timely

outbreak investigation


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Detecting an outbreak

DetectionRoutine surveillance

Clinical/laboratory

Rumor verification

General public

Media

Is this an

Outbreak?


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Is it an outbreak?

More than expected cases Illustrates the importance of surveillance and timely

analysis

Clustered in time, place or person

Pattern recognition

Concern from a HCW, school or media

Rumour verification

Encourage participation in the system


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Why investigate outbreaks?

Stop the outbreak (new cases)

Increase our knowledge

Prevent new episodes Evaluate the surveillance system

Establish a surveillance system

L

earn field epidemiology by doing


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Specific objectives of an investigation

Identify:

Causal agent

Mode of transmission

Source

Carrier

Population at risk

Exposure causing disease (risk factors)


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Real time vs. retrospective

investigation

Outbreaks in existence for several

days, weeks, months.

Based on the memory of the people

Data already collected

To be or not to be used

It is never to late,

but it can also be more difficult


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Preparation

Collect preliminary information Available data

Consult experts (microbiologist, veterinarian,entomologist etc)

Check search engines e.g., PUBmed

Search from both formal and informal surveillancesystem (event based and indicator based)

Prepare a short memo

Inform the concerned

Get authorization, travel itinerary

Investigation committee

Multidisciplinary Assign person in charge

Define tasks


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Example: Community epidemic due to S.

Typhimurium, Jura, May-June 1997

Context

Alert: PH medical officer

80 cases of salmonellosis in 5 weeks

Salmonella Typhimurium

Clustered in the South department of Jura

No connection (a priori) among cases

Pressure of media, of politicians

L

ocal Department of Public Health, VeterinaryServices, Centre National Reference, National

Institute of Public Health


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Steps in Outbreak Investigation

Descriptive steps

1) Determine existence of an outbreak

2) Confirm the diagnosis:

Which diseases are we talking about?

3) Define a case; find and count cases

4) Orient data as to:

Time (When?) Place (Where?)

Person (Who?)

the sequence is not important !


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Analyse5) Generate hypotheses

6) Test the hypotheses

7) Compare each hypothesis with facts

8) Plan a more systematic study

Synthesis and action

9) Write a report, communicate findings10) Control measure and prevention

Steps in Outbreak Investigationthe sequence is not important !


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1. Determine existence of an outbreak

Outbreak n observed cases > n expected cases

Expected cases? Surveillance data

Clinicians, hospital registers Hospital investigation, lab, doctors, schools..

Be careful of artefacts! Seasonal variation: (diarrhoea)

Notification variation: (new surveillance system inplace) Diagnostic variation: (new technique) Diagnostic mistake: (false epidemic")


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Number ofLegionella cases per week, France

January 1996 August 1997


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2. Confirm the diagnosis

Laboratory serology

isolation, serotype, lysotype, etc.

toxic agent

Meet the doctors

See the patients

Visit the laboratories

It is not necessary to confirm all the cases


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3. Define a case; find and count cases

A case definition is a standard set of criteria for

deciding whether an individual should be

classified as having the health condition of

interest Includes:

clinical criteria

restrictions by time, place and person (epidemiological

link)

laboratory findings (generally)


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Suspected

cases clinical case

definition enough for

immediate action

Confirmed

cases Collect relevant

samples laboratory

few cases (10-20)

Do not wait for laboratory results tostart treatment and control activities!

3.1. Define a case


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Example: Case DefinitionOutbreak of S. Typhimurium, Jura, May-June 1997

Confirmed Probable

Clinical Diarrhoea (> 2 liquidstools/day)

or Fever > 38C ( + one

day)

Diarrhoea (> 2 liquid

stools/day)

or Fever > 38C ( + one

day)

AND

Place,

Person

resident in Jura or

neighbourhood

resident in Jura or

neighbourhood

Time Since 12 May 1997 Since 12 May 1997

Biological Identification of S.Typhimurium

None, but contact with

confirmed case


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3.2. Find and count the cases

Information sources All possible sources (NGOs, local leaders, etc) Hospitals, health centres, laboratories, doctors,

nurses schools, camps, settlements Radio, door to door

snow ball Laboratory

How many? No strictly all

Collected information

Demographics clinical and biological

eventual exposure


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4. Orient data as to:

Time

Place

Persons


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4.1 Data description: TIME

epidemic curve

Case distribution over time (according tothe date - hour, week - of onset of signs)

Onset, peak, importance, time, end of

epidemic Abnormal cases

Allow to make hypothesis: incubation period, pathogen responsible

source, mode of transmission time of exposure

Epidemic evolution


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Example: Epidemic curve of Cases due to S.Typhimurium

by week of onset of symptoms of isolated bacteria,

Jura, May- June 1997.N o m b r e d e c a s

3 0

1 c a s

2 5

2 0

1 5

1 0

5

1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8

A v r i l M a i J u in J u i l le t

S e m a i n e s d is o l e m e n t o u d e d b u t d e s s y m p t m e s

One Case

April May June July

Number of Cases


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4.2 Data description: PLACE

Residence

Place of exposure

work, food places, journeys, tour Maps (mud maps, points, attack rate)

Identify areas at risk,Identify population at risk

Identify priority areas for control activities


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4.3 Data description: PERSON

Distribution of cases by age, sex, profession,etc (Numerator) ex: 50 women, 100 men

Distribution of variables in the population from

where cases are coming (Denominator) ex: 1500 women, 1000 men

Compute attack rate ex: women 50/1500 , men 100/1000

=> Identification of sub-group(s) at risk


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Example: Data Description - Person

Infection by S.Typhimurium

Attack Rate by age group, Jura, May-June 1997

Age group

(years)

Number of

Cases

65 9Total 98


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Example: Data Description - Person

Infection by S.Typhimurium,

Attack Rate by age group, Jura, may-June 1997

Age Group

(years)

Number of Cases Population Attack Rate/

100,000

65 9 41,948 22Total 98 246,858 40


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5. Generate hypotheses

Starting from: Descriptive information (TPP) Knowledge of the disease

Exploratory study on some cases

Explaining: Causal agent

Source

Way of transmission

Carrier

DIFFICULT !!!!


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Example: Generating Hypothesis

Infection of S.Typhimurium

Descriptive data: Agent: S. Typhimurium lysotype 12 atypical

Time, epidemic curve: persistent commonsource

Place: cases clustered in the south of Jura

Persons: Attack rate higher among children

All ages affected

Muslim among the cases


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Example: Formulating Hypothesis

Infection S.Typhimurium

May June 1997

Descriptive information Hypothesis

S. Typhimurium Meat (cow), salami, poultry,

milk products, etc

South of Jura Regional products, local

distribution

Children more affected Consumed products (also) by

some children

Muslim among cases Pork less probable

Good weather condition Barbecue, poultry

Documentation Epidemic of roasted poultry

described


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5. Generate HypothesisExploratory Survey

Formulate hypothesis

Interview some cases:

Open questionnaire and complete

Common exposure?

Example Jura:

Big questionnaire, inclusion of regionalproducts (cheese)

17 cases interviewed


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Example: Results of Exploratory Survey

Exposure of cases to specific food

Jura, May - June 1997

Food No. of cases

who ate

No. of

respondents

% of cases

exposed

Chipolatas 6 15 40

Cooked chicken 5 17 29

Raw chicken 7 16 44

Minced beef 7 17 41

Pork 9 17 53

Veal 8 17 47

Cheese (comte) 13 17 77Cheese A

(Fromage a)14 16 88

Rochfort (Bleu de

Gex)6 10 60


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6. Test the hypothesis

Objectives

Specific exposure: the carrier and the source Factors facilitating or protective

host, agent, environment

Survey to identify aetiology:

Cohort uses attack rates best in a small, well-defined population

Case-control odds ratio quantifies the relationship b/w exposure and

disease


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6. Test the hypothesis

Case-control

Compare Proportion of exposed among cases

Proportion of exposed among the non cases (controls)

Compute Odds Ratio (OR) and Confidence Interval(CI) at 95%

Select controls Not sick

Susceptible (e.g., not immunised)

Coming from the same population of cases

The same chances of being exposed


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Exposure of Cases and Controls to specific food

Jura, May - June 1997

Food No (%) of

exposed cases

Odds Ratio CI 95%

(N = 42) (N = 42)

Pats 11 (26) 17 (40) 0.5 0.2 1.3

Sausage 24 (57) 28 (67) 0.7 0.3 1.6

Beef 32 (78) 33 (79) 1 0.3 3.5

Pork 23 (59) 29 (76) 0.5 0.2 1.5

Veal 22 (54) 19 (46) 1.4 0.6 3.4

Chicken 30 (71) 34 (81) 0.6 0.2 1.7

Munster(cheese)

4 (10) 1 (2) 4.0 0.5 35.8

Bleu de Gex(blue cheese)

12 (35) 10 (24) 3.0 0.6 14.9

Comt (cheese) 36 (86) 37 (88) 0.8 0.3 2.7

Fromage A(cheese)

33 (83) 23 (55) 6.5 1.4 28.8


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7. Compare the hypothesis with facts

Compare the results clinical observation

biological examinations

epidemiological studies

statistical tests

The hypothesis should be:

plausible

biologically acceptable explain causal agent, source,

mode transmission, time of exposure


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Example:

Comparison of hypotheses with observed facts,

Jura, May-June 1997

Cheese A

Raw milk (plausible)

Consumed by children (meets personsaffected by the outbreak)

Regional product(meets place affected)

Collect cheese among the cases (datamicrobiological) S. Typhimurium identified in 3 cheeses A

Other cheeses negatives


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8. Plan a more systematic study

At the same time, and oriented by theepidemiological survey

Environmental survey

Microbiological survey

Plan more systematic studies (if needed)

More cases, more controls

Dose-effect, facilitating factors..


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Example: Complementary studies

Epidemic of S. Typhimurium

Jura, May-June, 1997

Microbiological survey: Food collection among cases

Sample collection among cases suppliers

Comparison of human specimens and food

products

Survey on the distribution network of cheese A

Survey among the producers: Veterinary Labour medicine

Environmental


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Survey distribution network

CREMERIE

Wholesaler

Cheese

dairy

Example: Complementary studiesEpidemic of S. Typhimurium

Jura, May-June, 1997


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9. Write a report; communicate findings

To be written on site

Promotes synthesis (of the objectives)

Documents the event(for evaluation/ legalpurposes)

Allows communication of results

Provides recommendations

Pedagogical tool (training material)


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10. Control measures and prevention

Dont wait for the end of the investigation : General measures at beginning Specific measures according to the results

Kinds of measures to control : The source (e.g.: chlorination of water)

The transmission (e.g.: hygiene measures) The carrier (e.g.: recall a lot of suspected cheese)

Reduce the susceptibility of host (e.g.: vaccination)

Communicate risk if outbreak is affecting the public

Example Jura:

Personal Hygiene Adequate cooking of meat

Recall of the incriminated product (Fromage A)


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" The art of epidemiological reasoning is tomake some reasonable conclusions

starting from imperfect data"

George W. Comstock (1915-2007)Physician and Professor Emeritus

Johns Hopkins Bloomberg School ofPublic Health


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But better information leads to better results

This means having: A good description of Time, Place, Person

(TPP)

Good data collection and preservation ofsamples

A well coordinated multidisciplinary team

Immediate

detection

Immediate

response

Reduced morbidity

and mortality


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0

10

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6070

80

90

1 4 7 10 13 16 19 22 25 28 31 34 37 40

DAY

CASES

LabConfirmation

Outbreak Detection and Response

Response

Opportunity

for control

Detection/Reporting

First

Case


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0

10

20

30

40

50

60

70

80

90

1 4 7 10 13 16 19 22 25 28 31 34 37 40

DAY

CASES

Outbreak Detection and Response

First

CaseDetection/

ReportingLabConfirmationResponse Opportunity

for control


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Ethical Aspect

Securing consent (participants)

Informing local authorities,

communities

Ethical treatment of animals


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Best practices

Establish clear and concise policies andprocedures

Careful documentation and proper

recording of events/results Effective communication skills

Evaluate and review responses

Expect the unexpected Key people away, new, emerging pathogen,

demystifying rumour, etc.


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References

De Valk, Henriette, French Institute for

Public Health Surveillance (Institut de veille

sanitaire, InVS)

European Programme on Intervention

Epidemiology Training


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Outbreak Investigation Best Practices/ Methods

SEARO CSR Training on Outbreak Investigation

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