1. This presentation is made available through a Creative Commons Attribution- Noncommercial license. Details of the license and permitted uses are available at http://creativecommons.org/licenses/by-nc/3.0/ © 2010 Dr. Juliet Pulliam and the Clinic on the Meaningful Modeling of Epidemiological Data http://creativecommons.org/licenses/by-nc/3.0/ Title: Introduction to Infectious Disease Data Attribution: Dr. Juliet Pulliam, Clinic on the Meaningful Modeling of Epidemiological Data Source URL: http://lalashan.mcmaster.ca/theobio/mmed/index.php/IntroIDDatahttp://lalashan.mcmaster.ca/theobio/mmed/index.php/IntroIDData For further information please contact Dr. Juliet Pulliam (juliet.mmed.clinic@gmail.com).

2. Introduction to infectious disease data Clinic on the Meaningful Modeling of Biological Data and BSc Honours Course in Biomathematics African Institute for the Mathematical Sciences Muizenberg, South Africa 26 May 2010 Dr. Juliet Pulliam RAPIDD Program, DIEPS Fogarty International Center, NIH, USA and Department of Ecology & Evolutionary Biology University of California at Los Angeles (UCLA)

3. What is an infectious disease?

4. Disease A deviation from the normal physiological status of an organism that negatively affects its survival or reproduction

5. Disease A deviation from the normal physiological status of an organism that negatively affects its survival or reproduction Infectious Disease A disease in one organism (the host) that is caused by another organism (pathogen or parasite) which has entered the host’s body

6. Case definition “a set of standard criteria for deciding whether a person has a particular disease [or infection]”

7. Case definition “a set of standard criteria for deciding whether a person has a particular disease [or infection]” Person: Place: Time: Clinical description:

8. A “case” study

9. Case definition “a set of standard criteria for deciding whether a person has a particular disease [or infection]” Person: Residents of Mexico, recent visitors to Mexico Place: North America (Mexico, US, Canada) Time: On or after March 15, 2009 Clinical description: severe influenza-like illness (fever, cough, sore throat, body aches, headache, chills, fatigue, and/or severe respiratory distress)

10. Sunday, 26 April

11. Confirmed case: signs and symptoms plus laboratory confirmation Probable case: signs and symptoms in an individual meeting person, place, and time criteria plus contact with a known case or more specific clinical signs Possible case: signs and symptoms in an individual meeting person, place, and time criteria plus a physician diagnosis Suspect case: signs and symptoms in an individual meeting person, place, and time criteria Not a case: failure to fulfill the criteria for a confirmed, probable, possible, or suspect case

12. Sunday, 26 April

13. Monday, 27 April

14. Tuesday, 28 April

15. Wednesday, 29 April

16. Thursday, 30 April

17. Friday, 1 May

18. Saturday, 2 May

19. Sunday, 3 May

20. Monday, 4 May

21. Tuesday, 5 May (?) 14 1 1 X

22. ? ? Monday, 4 May

23. Case definition “a set of standard criteria for deciding whether a person has a particular disease [or infection]” Person: Place: Time: Clinical description:

24. Case definition Person: Residents of and recent visitors to North America, and their close contacts or others in their community Place: Worldwide Time: On or after March 15, 2009 Clinical description: fever, cough, sore throat, body aches, headache, chills, fatigue, and/or severe respiratory distress; diarrhea and vomiting do not rule out diagnosis

25. Incidence of disease Date of onset

26. Mathematical expression? Incidence of infection

27. Ways of collecting data on cases Surveillance Hampson et al. 2009 Surveillance + Contact Tracing/Outbreak investigation

28. Ways of collecting data on cases Epidemiological studies

29. Prevalence of infection of disease of antibodies (seroprevalence) Mathematical expression? Source: UNAIDS HIV Surveillance Database

30. Seroprevalence Can be related to: Prevalence of infection Past exposure May or may not be: Prevalence of resistance Specific to infection of interest

31. Seroprevalence Can be related to: Prevalence of infection Past exposure May or may not be: Prevalence of resistance Specific to infection Pulliam et al. (In review)

32. Seroconversion Mathematical expression?

33. Levels of data aggregation Aggregated data De-identified data Personally identifying data

34. Sources Slides 8 and 10-22: Images are reproduced from The New York Times (online edition), April 2009. Slide 25: Data are available from The Centers for Disease Control and Prevention, Atlanta, GA, USA. www.cdc.gov/flu/weekly - Image available at: http://www.cdc.gov/flu/weekly/weeklyarchives2008-2009/weekly36.htmwww.cdc.gov/flu/weekly Slide 27: Hampson et al. (2009) Transmission dynamics and prospects for the elimination of canine rabies. PLoS Biology 7(3): e1000053. doi:10.1371/journal.pbio.1000053 Slide 29: Data from UNAIDS HIV Surveillance Database, provided courtesy of USAID. Slide 31: Pulliam et al. (In review) Agricultural intensification, priming for persistence, and the emergence of Nipah virus, a lethal bat-borne zoonosis.