**Core Concept**
Sensitivity is a key concept in epidemiology and biostatistics, measuring the ability of a diagnostic test or screening program to detect true cases or individuals with a particular disease or condition. It is an essential metric for evaluating the effectiveness of screening tests in reducing morbidity and mortality.

**Why the Correct Answer is Right**
Sensitivity specifically refers to the proportion of true positive results among all actual positives, which means it measures the ability of a test to correctly identify individuals who have the disease. This is crucial in public health and preventive medicine, as it helps in early detection and intervention. Sensitivity is calculated as the number of true positive results divided by the sum of true positive and false negative results (TP / (TP + FN)). A high sensitivity test can detect most cases, enabling prompt treatment and reducing the risk of complications.

**Why Each Wrong Option is Incorrect**
**Option A:** True negative refers to the proportion of individuals without the disease who are correctly identified as such by the test. Sensitivity does not measure this aspect.

**Option C:** False negative refers to individuals with the disease who are incorrectly identified as not having it. While false negatives are an issue, sensitivity specifically measures the ability to detect true positives, not the opposite.

**Option D:** False positive refers to individuals without the disease who are incorrectly identified as having it. Like true negatives, false positives are not relevant to sensitivity.

**Clinical Pearl / High-Yield Fact**
When evaluating a screening test, consider both sensitivity and specificity. A test with high sensitivity will detect most cases but may produce false positives, while a test with high specificity will produce few false positives but may miss some cases.

**✓ Correct Answer: B. True positive. The ability to detect true positives is the essence of sensitivity in epidemiology and public health.**