The term sensitivity in epidemiology is a statistical measure on individuals who are positive, and they test positive in the tests. On the other hand, specificity refers to a statistical measure of individuals who tests negative and are truly negative.

Any medical test that is conducted within the research field is adjusted toward the two options. A test that is structured to be highly sensitive is geared toward determining the actual number of people infected by a particular disease during an outbreak. Specificity is geared in determining the actual number of people free of the disease.

The two tests are used in the epidemiological field to assess the strength of the test used. Sensitivity is given by the following formula:

Sensitivity = TP/TP+FN, where TP means true positive, and FN means false negative. Sensitivity in a medical test gives a high confidence rate that the results of the conducted tests are truly positive and the individual has the disease. On the hand Specificity is obtained through the following formula; or Specificity =TN/TN+FP, where, FN means False Negative. Specificity in a medical test gives the surety that the results obtained by the tests are truly negative. This means the individual is free from the disease.

The two tests are further used in other epidemiological tests such as the positive predictive value (PPV) and the negative predictor value (NNV).