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Outbreak Investigation

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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  1. Outbreak Investigation Best Practice/Methods Practical Reference Points

  2. 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

  3. Detecting an outbreak Routine surveillance Clinical/laboratory Rumor verification General public Media Detection Is this an Outbreak?

  4. 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

  5. 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

  6. Specific objectives of an investigation Identify: • Causal agent • Mode of transmission • Source • Carrier • Population at risk • Exposure causing disease (risk factors)

  7. 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

  8. 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

  9. 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

  10. 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?)

  11. 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

  12. 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")

  13. Number of Legionella cases per week, France January 1996 – August 1997

  14. 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

  15. 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)

  16. 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!

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

  18. 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

  19. 4. Orient data as to: • Time • Place • Persons

  20. 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

  21. 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

  22. 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

  23. 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

  24. Example: Data Description - PersonInfection by S.TyphimuriumAttack Rate by age group, Jura, May-June 1997

  25. Example: Data Description - Person Infection by S.Typhimurium, Attack Rate by age group, Jura, may-June 1997

  26. 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 !!!!

  27. 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

  28. Example: Formulating HypothesisInfection S.Typhimurium May – June 1997

  29. 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

  30. Example: Results of Exploratory Survey Exposure of cases to specific foodJura, May - June 1997

  31. 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

  32. 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

  33. Exposure of Cases and Controls to specific foodJura, May - June 1997

  34. 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

  35. 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

  36. 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..

  37. 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

  38. Survey distribution network Example: Complementary studiesEpidemic of S. TyphimuriumJura, May-June, 1997 Wholesaler Cheese dairy CREMERIE

  39. 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)

  40. 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)

  41. " 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

  42. 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

  43. Outbreak Detection and Response First Case Detection/ Reporting Lab Confirmation Response Opportunity for control CASES DAY

  44. Outbreak Detection and Response First Case Detection/ Reporting Lab Confirmation Response Opportunity for control CASES DAY

  45. Ethical Aspect • Securing consent (participants) • Informing local authorities, communities • Ethical treatment of animals

  46. 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.

  47. 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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