Epidemiology Study Guide

History and Foundations of Epidemiology

John Snow, Semmelweis, Goldberger; definition, uses, and population perspective essential for understanding epidemiologic thinking on exams.

Measures of Disease Frequency

Incidence, prevalence, mortality rates, and their relationships; fundamental calculations appearing in every exam's quantitative sections.

Measures of Association

Risk ratio, odds ratio, attributable risk, NNT calculations from 2×2 tables; core quantitative skills tested extensively.

Descriptive Epidemiology

Person-place-time analysis, epidemic curves, case reports; hypothesis generation skills tested through data interpretation questions.

Cohort Studies

Prospective and retrospective designs, person-time calculation, strengths and limitations; frequent exam questions on design identification.

Case-Control Studies

Case and control selection, odds ratio interpretation, matched analysis; exam staple for bias scenarios and calculations.

Cross-Sectional and Ecological Studies

Prevalence surveys, ecologic fallacy, study limitations; commonly tested for design critique and appropriate inference questions.

Experimental Studies and Clinical Trials

RCT design, randomization, blinding, intention-to-treat analysis; ethical considerations and CONSORT guidelines tested on exams.

Bias in Epidemiologic Studies

Selection and information bias types, misclassification effects; critical evaluation scenarios dominate exam study critique questions.

Confounding and Effect Modification

Identifying, assessing, and controlling confounding; distinguishing from interaction; stratified analysis interpretation essential for exams.

Causal Inference

Hill's criteria, component cause model, DAG basics; exam questions assess ability to evaluate causation claims.

Screening, Surveillance, and Outbreak Investigation

Sensitivity, specificity, predictive values, outbreak steps, attack rate tables; applied scenarios common on final exams.