A true positive occurs when a test correctly identifies a positive case—that is, the test detects the condition when it is truly present. It is one of the four mutually exclusive outcomes in a confusion matrix, which categorizes test results into: true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN).
True positives are essential for calculating test performance metrics such as sensitivity, positive predictive value (PPV), and overall accuracy. These measures assess how effectively a test detects real cases of the condition it aims to identify.
For example, a true positive result in a COVID-19 test means the person who actually has the virus was correctly identified. This is beneficial because it allows for timely isolation and treatment, which can reduce spread and improve health outcomes.
