Preventive Medicine and Public Health: Populations and Probability
Priority concepts
Know the levels of prevention: primordial and primary act before disease, secondary detects early disease, tertiary limits complications, and quaternary avoids overmedicalisation. Screening programmes are judged against demanding criteria - an important condition, a suitable test with acceptable performance, an effective treatment, and evidence that earlier detection changes outcome. Be fluent with incidence, prevalence, sensitivity, specificity, and predictive values, and with biases that distort screening claims: lead-time bias, length bias, and overdiagnosis.
Outbreak investigation follows a sequence: confirm the diagnosis, define and find cases, describe by person, place, and time, generate hypotheses, test them, and implement control. Vaccination questions test schedule timing, live versus inactivated vaccines, contraindications, and herd immunity thresholds.
Traps
Confusing incidence with prevalence is routine. Predictive values are prevalence-dependent, so a highly specific test used in a low-prevalence population produces many false positives. Also distinguish association from causation and remember that a reduced mortality rate in screened patients may reflect earlier diagnosis rather than longer life.
Worked example
A test with 90% sensitivity and 95% specificity is applied in 10,000 people where prevalence is 1%. There are 100 cases: 90 detected, 10 missed. Of 9,900 without disease, 5% (495) test positive falsely. Positive predictive value = 90/(90 + 495) ≈ 15%. Most positives are false, which is why confirmatory testing follows screening.
Rule of thumb
Sensitivity rules out when negative; specificity rules in when positive; predictive values depend on how common the disease is in the population you are testing.