Understanding COVID Test Accuracy: Sensitivity, Specificity, and Bayesian Theorem

The chapter breaks down the components of test accuracy - sensitivity and specificity - in determining COVID test results. It emphasizes the importance of prevalence information for accurate interpretation and explains how Bayesian theorem can convert sensitivity into positive predictive value. Through simple analogies and scenarios, the chapter clarifies the difference between sensitivity, specificity, and positive predictive value for accurate result assessment.