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Analysis of Surveillance Data

Analysis of Surveillance Data. Philippe Dubois From Denis Coulombier, Julia Fitzner, Augusto Pinto & Marta Valenciano, WHO-HQ/LYON. Analysis of Surveillance Data. Data characteristics Data validation Descriptive analysis Hypothesis testing. Data Characteristics.

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Analysis of Surveillance Data

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  1. Analysis of Surveillance Data Philippe Dubois From Denis Coulombier, Julia Fitzner, Augusto Pinto & Marta Valenciano, WHO-HQ/LYON Phom Penh, Cambodia

  2. Analysis of Surveillance Data • Data characteristics • Data validation • Descriptive analysis • Hypothesis testing

  3. Data Characteristics • Various sources of notification • Various levels of qualification • Continuous data collection subject to change

  4. Surveillance Data Validation • Frequency distributions • missing values • expected distribution • digit attraction • Cross-Tabulations • age, sex, logical errors • by source: collect bias ?

  5. Notifications of All Notifiable Diseasesby Date of Onset, USA, 1989

  6. Birth weight Distribution, in PoundsFermattes Hospital, Haiti, February 1994

  7. Descriptive Approach • Time • Place • Persons • Generating hypotheses

  8. Analyzing Time Characteristics • Graphical analysis • The 3 data components • secular trend • seasonal variations • accidental variations

  9. Notifications of Foodborne Outbreaks in France, 1996-1998

  10. Notifications of Foodborne Outbreaks in France, 1996-1998 1996 1997 1998

  11. Components of Surveillance Data • Signal • secular trend • seasonal variations • accidental variations

  12. Decomposition of Surveillance Data Signal

  13. Descriptive analysis of Components • Moving averages • empirical method • for reducing variability • same area under the curve • Logarithmic scale • dynamic analysis of changes • difficult to interpret

  14. Calculation of moving averages 822 Jan 654 Feb Apr 546 3622/5=724,4 728 3690/5=738.0 Mar 3836/5=767.2 May 872 Jun 890 1993 Jul 692 465 Aug Sep 869 5 month window Oct 726 Nov 834 Dec 945

  15. Notification of giardiasis in Delaware, 03/1991-03/1995 Crude Weekly Data

  16. Notification of giardiasis in Delaware, 03/1991-03/1995 12 Week Moving Average

  17. Notification of giardiasis in Delaware, 03/1991-03/1995 52 Week Moving Average

  18. Notification of giardiasis in Delaware, 03/1991-03/1995 Aggregated data

  19. Size of the Moving Average Window 1. Showing cyclical variations by removing accidental variations • empirical approach: the visual impression • inversely proportional to the number of cases • increases as the variance increases

  20. Effect of the Moving Average Window Size Weekly Notifications of Salmonellosis, Georgia, 1993-1994 3 weeks 5 weeks 7 weeks 10 weeks

  21. Size of the Moving Average Window 2. Showing secular trend by removing cyclical variations • Cycle span • 52 for weekly data • 12 for monthly data • 4 for quarterly data

  22. Week 10 of 1994 and 208 Previous Weeks Cases of Gonorrhea in Michigan

  23. Cases of Gonorrhea in Michigan Week 10 of 1994 and 208 Previous Weeks

  24. Descriptive Analysis of the 3 Components • Moving average • empirical method • variability reduction • same area under the curve • Logarithmic scale • dynamic analysis of changes • difficult to interpret

  25. Annual Rate of Tuberculosis, United States, 1940-1990

  26. Annual Rate of Tuberculosis, United States, 1940-1990

  27. MALARIA- By year, United States, 1930-1992

  28. MALARIA- By year, United States, 1930-1992 MALARIA- By Year, United States, 1930-1992

  29. GONORRHEA - By race and ethnicity, United States, 1981-1993 Arithmetic scale

  30. GONORRHEA - By race and ethnicity, United States, 1981-1993 GONORRHEA - By race and ethnicity, United States, 1981-1993 Logarithmic scale Source: Summary of Notifiable Diseases, United States 1993

  31. Typhoid Notifications in France

  32. Typhoid Notifications in France Typhoid Notifications in France

  33. Interpreting the results • Role of chance • Role of bias • True disease pattern

  34. Conclusions • Analysis to draw attention • Validation by investigation

  35. Questions? Comments? Discussions?

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