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Outbreak Investigation. Best Practice/Methods Practical Reference Points. 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

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Outbreak Investigation


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outbreak investigation

Outbreak Investigation

Best Practice/Methods

Practical Reference Points

learning objectives
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
detecting an outbreak
Detecting an outbreak

Routine surveillance

Clinical/laboratory

Rumor verification

General public

Media

Detection

Is this an

Outbreak?

is it an outbreak
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
why investigate outbreaks
Why investigate outbreaks?
  • Stop the outbreak (new cases)
  • Increase our knowledge
  • Prevent new episodes
  • Evaluate the surveillance system
  • Establish a surveillance system
  • Learn field epidemiology by doing
specific objectives of an investigation
Specific objectives of an investigation

Identify:

  • Causal agent
  • Mode of transmission
  • Source
  • Carrier
  • Population at risk
  • Exposure causing disease (risk factors)
real time vs retrospective investigation
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

preparation
Preparation
  • Collect preliminary information
    • Available data
    • Consult experts (microbiologist, veterinarian, entomologist etc)
    • Check search engines e.g., PUBmed
    • Search from both formal and informal surveillance system (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
example community epidemic due to s typhimurium jura may june 1997
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
  • Local Department of Public Health, Veterinary Services, Centre National Reference, National Institute of Public Health
steps in outbreak investigation
Steps in Outbreak Investigation

the sequence is not important !

  • Descriptive steps
    • Determine existence of an outbreak
    • Confirm the diagnosis:
      • Which diseases are we talking about?
    • Define a case; find and count cases
    • Orient data as to:
      • Time (When?)
      • Place (Where?)
      • Person (Who?)
steps in outbreak investigation the sequence is not important
Steps in Outbreak Investigation the sequence is not important !
  • Analyse
    • Generate hypotheses
    • Test the hypotheses
    • Compare each hypothesis with facts
    • Plan a more systematic study
  • Synthesis and action
    • Write a report, communicate findings
    • Control measure and prevention
1 determine existence of an outbreak
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 in place)
    • Diagnostic variation: (new technique)
    • Diagnostic mistake: (“false epidemic")
2 confirm the diagnosis
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

3 define a case find and count cases
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)
3 1 define a case
Suspected cases

clinical case definition

enough for immediate action

Confirmed cases

Collect relevant samples

laboratory

few cases (10-20)

3.1. Define a case

Do not wait for laboratory results to

start treatment and control activities!

3 2 find and count the cases
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
4 orient data as to
4. Orient data as to:
  • Time
  • Place
  • Persons
4 1 data description time epidemic curve
4.1 Data description: TIME epidemic curve
  • Case distribution over time (according to the 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
slide21
Example: Epidemic curve of Cases due to S.Typhimurium by week of onset of symptoms of isolated bacteria, Jura, May- June 1997.

Number of Cases

One Case

April

May

June

July

4 2 data description place
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

4 3 data description person
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

slide24
Example: Data Description - PersonInfection by S.TyphimuriumAttack Rate by age group, Jura, May-June 1997
slide25
Example: Data Description - Person Infection by S.Typhimurium, Attack Rate by age group, Jura, may-June 1997
5 generate hypotheses
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 !!!!

example generating hypothesis infection of s typhimurium
Example: Generating HypothesisInfection of S.Typhimurium
  • Descriptive data:
    • Agent: S. Typhimurium lysotype 12 atypical
    • Time, epidemic curve: persistent common source
    • Place: cases clustered in the south of Jura
    • Persons:
      • Attack rate higher among children
      • All ages affected
      • Muslim among the cases
5 generate hypothesis exploratory survey
5. Generate HypothesisExploratory Survey
  • Formulate hypothesis
  • Interview some cases:
    • Open questionnaire and complete
  • Common exposure?

Example Jura:

  • Big questionnaire, inclusion of regional products (cheese)
  • 17 cases interviewed
6 test the hypothesis
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 ratioquantifies the relationship b/w exposure and disease
6 test the hypothesis case control
6. Test the hypothesisCase-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
7 compare the hypothesis with facts
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
example comparison of hypotheses with observed facts jura may june 1997
Example: Comparison of hypotheses with observed facts, Jura, May-June 1997

Cheese A

  • Raw milk (plausible)
  • Consumed by children (meets persons affected by the outbreak)
  • Regional product (meets place affected)
  • Collect cheese among the cases (data microbiological)
    • S. Typhimurium identified in 3 cheeses A
    • Other cheeses negatives
8 plan a more systematic study
8. Plan a more systematic study
  • At the same time, and oriented by the epidemiological survey
    • Environmental survey
    • Microbiological survey
  • Plan more systematic studies (if needed)
    • More cases, more controls
    • Dose-effect, facilitating factors..
example complementary studies epidemic of s typhimurium jura may june 1997
Example: Complementary studiesEpidemic of S. TyphimuriumJura, 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
survey distribution network
Survey distribution network

Example: Complementary studiesEpidemic of S. TyphimuriumJura, May-June, 1997

Wholesaler

Cheese dairy

CREMERIE

9 write a report communicate findings
9. Write a report; communicate findings
  • To be written on site
  • Promotes synthesis (of the objectives)
  • Documents the event (for evaluation/ legal purposes)
  • Allows communication of results
  • Provides recommendations
  • Pedagogical tool (training material)
10 control measures and prevention
10. Control measures and prevention
  • Don’t 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)
slide41

" The art of epidemiological reasoning is to make some reasonable conclusions

starting from imperfect data"

George W. Comstock (1915-2007)

Physician and Professor Emeritus

Johns Hopkins Bloomberg School of Public Health

but better information leads to better results
But better information… leads to better results
  • This means having:
    • A good description of Time, Place, Person (TPP)
    • Good data collection and preservation of samples
    • A well coordinated multidisciplinary team

Immediate detection

Immediate response

Reduced morbidity and mortality

outbreak detection and response
Outbreak Detection and Response

First

Case

Detection/

Reporting

Lab

Confirmation

Response

Opportunity

for control

CASES

DAY

outbreak detection and response44
Outbreak Detection and Response

First

Case

Detection/

Reporting

Lab

Confirmation

Response

Opportunity

for control

CASES

DAY

ethical aspect
Ethical Aspect
  • Securing consent (participants)
  • Informing local authorities, communities
  • Ethical treatment of animals
best practices
Best practices
  • Establish clear and concise policies and procedures
  • 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.
references
References
  • De Valk, Henriette, French Institute for Public Health Surveillance (Institut de veille sanitaire, InVS)
  • European Programme on Intervention Epidemiology Training