Public Health, Epidemiology and Infection Prevention
Public health, epidemiology and infection prevention tests how disease is measured, how outbreaks are investigated, and how laboratories prevent transmission. Expect rates, screening statistics, sterilisation and waste management.
Core rules
- Incidence counts new cases over a period; prevalence counts all existing cases at a point. Attack rate is the proportion of exposed people who become ill during an outbreak.
- Sensitivity is the proportion of true cases detected; specificity the proportion of non-cases correctly called negative. Positive predictive value depends on prevalence, so the same test performs worse in a low-prevalence population.
- Outbreak investigation: confirm the diagnosis, define a case, describe by time, place and person, form a hypothesis, test it, control and report.
- Sterilisation kills all organisms including spores: autoclave at 121°C and 15 psi for 15 minutes, or hot air oven at 160°C for two hours. Disinfection reduces but does not eliminate spores.
- Standard precautions apply to every patient; hand hygiene is the single most effective measure. Sharps go into puncture-proof containers, and waste is segregated by category.
Worked example
A screening test with 95% sensitivity and 95% specificity is used in a population where prevalence is 1%. Of 10,000 people, about 100 have the disease; 95 are detected, but 495 of the 9,900 healthy people are false positives. Positive predictive value is 95/590, roughly 16%, so most positive results are wrong. The reasoning: low prevalence drives a low predictive value even for a good test, which is why confirmatory testing is essential.
Traps
Confusing incidence with prevalence; quoting sensitivity as if it predicted the chance a positive result is correct; and assuming a disinfectant is a sterilant.