1. Outbreak Investigation

2. Objectives  Determine if an outbreak is occurring  Characterise the outbreak  Identify additional cases  Identify causative agent  Identify the source  Initiate steps to terminate transmission  Learn for the future

3. Surveillance for disease  Certain infectious diseases pose significant threats to the health of the public  It is important that public health know about them  States, federal and international health authorities develop lists of reportable disease.

4. Surveillance  Physicians, hospitals and clinical laboratories are required to report, usually within a specified time period  Serious diseases are often categorized separately  Basic functions of communicable disease control at the state and local levels is the gathering and analysis of reportable disease data

5. Examples of Reportable Diseases in Michigan  Enteric diseases  Salmonellosis, shigellosis, Campylbacter, hepatitis A  Sexually Transmitted Diseases  Syphilis, gonorrhea, HIV  CNS diseases  Bacterial and viral meningitis, Arboviral – WNV, EEE  Vaccine Preventable Diseases  Measles, mumps, diphtheria, polio, hepatitis B

6. Collection and analysis of data  LHD receives reports  LHD logs and reviews data  Number of cases within a specific time period e.g a week  Geographic distribution of cases  Determination if the cases need further investigation  LHD send s reports to MDCH via LHDSurv (soon to be replaced by MDSS)  MDCH sends reports to CDC via NETSS

7. Data analysis  Need to know background level  Track weekly occurrence of disease over a number of years to establish an average number of cases per week for that particular week  Need to determine when the number of cases is above the background

8. Establish when an outbreak is occurring  For some diseases, a single case is an outbreak e.g measles, smallpox  In others, use the background as a threshold, but take into account other variables  e.g. is the gender or age frequency similar to previous years,  are the cases clustered geographically

9.  Sometimes the illness is reported before a disease is identified  Many calls from physicians and the public about persons becoming ill with diarrhea, vomiting  Using symptoms try to ascertain the likely disease  Get specimens to send to the laboratory if not already obtained

10. Investigation  Characterize the data that you have  Try to identify other similar cases occurring  How would you do this?  Fax to ERs  Notices on electronic boards

11. Case definition  What would you need in a case definition  Time  Place  Symptoms  E.g. All persons who experienced vomiting, diarrhea, nausea or abdominal cramping and who ate at Joe’s Greasy Spoon between Dec 10 and Dec 14.

12. Data Analysis  Determine which cases fit the case definition  Analyse by variables  Age  Gender  Race  Geography  Risk factor  Food  Drink  Behavior e.g. smoking, outdoor activity, attends day care

13. Data analysis  Frequencies  Incubation periods  Laboratory tests  Epidemic curve  Attack rates  By person  By place  By risk factor

14. Hypothesis  Using the data analysis, formulate hypotheses  Select the hypothesis which fits the picture  Hypothesis should address  Source of the disease  Etiologic agent  Method of transmission  Control methods

15. Hypothesis generation  Hypotheses can be generated at any time during the investigation, and refined as more data becomes available. But beware of making false assumptions  But don’t leave it too late, as hypothesis generation should lead to control measures

16. Hypothesis testing  Laboratory results can confirm the etiologic agent  Prevent further consumption of implicated food can confirm the transmission/source  Data analysis –  Case – control study using matched or unmatched controls.

17. Control methods  Initiate control methods based upon hypothesis

18. Report of findings  So others can learn from our experience