Community Medicine: Epidemiology, Screening, and Public Health
What this domain tests
The domain covers study design, measures of disease frequency, screening, outbreak investigation, health systems, and prevention. Calculations and interpretation of bias are common.
Core rules
- Incidence measures new cases; prevalence measures existing cases and depends on duration.
- Sensitivity detects disease; specificity detects absence. Predictive values depend on prevalence.
- Cohort studies estimate incidence and relative risk; case–control studies estimate odds ratios.
- Attack rate is the number of cases divided by the population at risk during an outbreak.
- Screening must be acceptable, safe, and effective, with a treatable preclinical phase.
Worked example
In a 1,000-person population, 200 have disease. A test is positive in 180 diseased and 80 non-diseased people. Sensitivity is 180/200 = 90%. Specificity is 720/800 = 90%. PPV is 180/(180+80) = 69%. The reasoning shows that even with 90% sensitivity and specificity, PPV falls when prevalence is low. If the same test were used in a high-prevalence clinic, PPV would rise without any change in sensitivity or specificity.
Traps
Confusing relative risk with odds ratio; saying PPV is fixed; ignoring lead-time and length bias in screening; calculating attack rate using the whole population instead of those at risk; mixing incidence and prevalence in follow-up studies.
Exam strategy
Write the 2×2 table before calculating. State whether the question asks about test performance or patient probability.