Community Medicine and Public Health
This domain tests measurement and programme logic: study designs, measures of disease frequency and association, screening statistics, and Nepal's public health programmes.
Core rules
- Incidence counts new cases over a period and measures risk; prevalence counts all existing cases at a point in time. Prevalence rises with longer duration and better survival.
- Cohort studies give relative risk; case-control studies give odds ratios; RCTs best control confounding but need randomisation and blinding.
- Screening: sensitivity and specificity are properties of the test; positive predictive value depends on prevalence.
- Nepal programmes: female community health volunteers deliver ORS, zinc and family planning; immunisation is delivered through the national schedule; tuberculosis follows DOTS with sputum monitoring; safe motherhood includes birth preparedness and the maternity incentive scheme.
Worked example
In 1,000 screened people, 100 have disease and 80 of them test positive; 90 of the 900 healthy people also test positive. Sensitivity = 80/100 = 80%. Specificity = 810/900 = 90%. PPV = 80/170 ≈ 47%. If prevalence fell to 1%, the same test would have a PPV of about 8/107 ≈ 7.5%.
Traps
- Reporting a relative risk from a case-control study.
- Assuming a good test always gives a high PPV.
- Confusing infant mortality rate with neonatal mortality rate.
- Ignoring confounding when a crude association looks strong.