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Epidemiology and Sex(ually Transmitted Diseases): The Basics

Epidemiology and Sex(ually Transmitted Diseases): The Basics . Willard Cates, Jr., MD, MPH Family Health International. Principles of STD/HIV Research University of Washington Seattle, Washington July 22, 2002. Objectives. To understand basic definitions of epidemiology

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Epidemiology and Sex(ually Transmitted Diseases): The Basics

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  1. Epidemiology and Sex(ually Transmitted Diseases): The Basics Willard Cates, Jr., MD, MPH Family Health International Principles of STD/HIV Research University of Washington Seattle, Washington July 22, 2002

  2. Objectives • To understand basic definitions of epidemiology • To describe components of descriptive, observational and experimental epidemiology • To know advantages and disadvantages of case-control and cohort designs

  3. Cholera in London, 1854

  4. The Etymology of Epidemiology epi = upon demos = people logy = study of e.g. Population Level Science

  5. Definition of Epidemiology The study of the distribution and determinants of disease and health in human populations. Stedman’s

  6. Epidemiology The science of making the obvious obscure Clinician

  7. Epidemiology I0 = (480)(2)/106/yr (9.1 x 0.955) + 0.045 The science of long division Statistician

  8. Epidemiology The worst-taught course in medical school Anonymous Med Student

  9. Epidemiology The study of skin diseases Atlanta Native

  10. Epidemiology’sFundamental Axioms • Non-randomness • Etiologic thinking • Preventability

  11. Epidemiology • Quantitative basic science • Method of causal reasoning • Vehicle for clinical and public health action W. Cates, 1982

  12. Exposure Variable – “E” • Characteristic of interest • Risk factor • Predictor variable • Independent variable • Putative causal factor

  13. Outcome or Disease Variable – “D” • Health event of interest • Illness, injury, infection • Response variable • Dependent variable • Effect variable

  14. E-D Relationships – STD Examples • Gonorrhea – PID • PID – ectopic pregnancy • Age – chlamydia infection • HPV – cervical cancer • Alcohol – high risk behavior • Circumcision – HIV infection

  15. Categories of Study Design • Descriptive • Analytic • Experimental

  16. Knowledge Continuum Less More Most     Descriptive Analytic Experimental • Search for clues • Clues available

  17. Descriptive Studies • Patterns of occurrence • No comparison group • Generate hypotheses about E-D relationships

  18. Descriptive Studies: Examples from STD • Epidemiology of chlamydia in Norway • Prevalence of sexual behaviors among a sample of the general population • Trends in the first 20 years of AIDS in the US

  19. Analytic Studies • Test hypotheses about E-D relationships • Three main types: – Cohort – Case-control – Cross-sectional

  20. Cohort Studies - Overview • Subjects selected on basis of E • Directionality always forward – E D • Timing – Prospective: “real time” – Retrospective: “historical time” 

  21. Cohort Studies – Flow Chart D+ Study Group E+ D Source Population D+ Study Group E D

  22. Cohort Studies: Major Advantages • Logical temporal sequence • Can measure incidence of D • Well-suited for rare E • Can study many effects of one E

  23. Cohort Studies: Major Disadvantages • Many subjects needed for rare D • Follow-up: logistics, losses • Prone to selection bias • Prospective: time-consuming, costly, observation can influence behaviors • Retrospective: suitable records

  24. Case-Control Studies:Overview • Subjects selected on basis of D • Directionality is backward –D E

  25. Case-Control Studies – Flow Chart E+ Cases D+ E Source Population E+ Controls D E

  26. Case-Control Studies: Major Advantages • Quick and inexpensive • Can study multiple E • Well-suited for rare D and D with long latency • Requires fewer subjects at entry

  27. Case-Control Studies: Major Disadvantages • Design “backward” • Unsuitable for rare E • Usually cannot measure D incidence • Temporal E-D uncertainty • Prone to selection and recall bias

  28. Study Bias - A Further Look • Selection bias: differential selection of participants on the basis of E or D • Information bias: differential collection or classification of E or D among participants –Recall bias: differential recall of E among cases and controls

  29. Experimental Studies (1) • Assign E randomly, follow for D • If placebo, blinding possible • Types: – Clinical trial – Community trial

  30. Experimental Studies (2) • Rolls Royce! • Randomization controls extraneous variables, both known and unknown • Limitations: ethical concerns, cost, length, not feasible for rare D

  31. Observational vs. Experimental: A Tale of 2 Studies StudyDesign Zekeng, 1993 Observational/Cohort Roddy, 1998 Experimental • Both were conducted in the same network of Cameroon sex workers • Both examined use of N-9 and HIV acquisition

  32. Initial Analysis of Observational Study Rate of HIV (per 100 women years) Inconsistent users 16.3 Consistent users 3.5 Rate Ratio 0.2 (0.1 – 0.7) Source: Zekeng (1993)

  33. Reanalysis of Observational Study • Data Source: Coital diaries from sex workers • Measure: Efficacy per sexual episode • Result: Condoms 92% (79-100%) • N-9 Suppositories 100% (43-100%) • Sources: Zekeng (1993), Wittkowski (1998)

  34. Observational Analysis of the 2 N-9 Studies • ZekengRoddy • Analysis Observational Observational • Rates of HIV: • Inconsistent use 16.3 15.6 • Consistent use 3.5 5.0 • Rate Ratios 0.2 (0.1-0.7) 0.3(0.1-0.7) • Sources: Zekeng (1993), Roddy (1998)

  35. Observational vs. Experimental Analysis, Same N-9 Study • RoddyRoddy • Analysis Observational Experimental • Rates of HIV: • Inconsistent use 15.6 Placebo 4.3 • Consistent use 5.0 N-9 5.3 • Rate Ratios 0.3 (0.1-0.7) 1.2(0.7-2.1) Source: Roddy (1998)

  36. Study Design:Concluding Remarks • Must consider: – Objectives of study – Current knowledge about E-D – Ethical issues – Time, money, human resources • Different approaches • Flexibility and creativity are KEY!

  37. Quality of Evidence I. Good evidence - large RCT, - primary outcomes II. Fair evidence - observational studies, - surrogate outcomes III. Weak evidence - anecdotes, - expert opinion Strength of Recommendation A. Stronger - important benefits, - broadly applicable B. Weaker - smaller benefit, - limited generalizability C. Insufficient evidence - expert opinion Uses of Epidemiology:Levels of Evidence

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