This calculator estimates the true prevalence of disease, given a) the test characteristics from a validation (test accuracy) study, followed by b) test results in a sample from the target population.

These confidence intervals use the adjustment to the Rogan-Gladen formulas proposed by Lang and Reiczigel.

a) Validation study. Run an antibody test T on cases known to have been infected (D+) to estimate sensitivity and controls known not to have been infected (D-) to estimate specificity.
b) Prevalence study. Now apply the test to a representative sample from the population of interest. To estimate true prevalence, the proportion of the sample with a positive test (T+) must be adjusted for the test's imperfect sensitivity and specificity.
Instructions: Enter parameters in the red cells. Answers will appear in blue below.
Test validation
Number of known infected cases in the validation study
TV+ & DV+
Number of positive test results among those cases

Number of known non-infected controls in validation study
TV− & DV
Number of negative test results among those cases
Sample size
Number of people tested in sample from target population.
Number of positive test results in population.
Raw prevalence
Point estimate of true prevalence in population:

Confidence interval per Reiczigel
Lower bound:
Upper bound:

Confidence interval per Rogan and Gladen
Lower bound:
Upper bound:
Rogan WJ, Gladen B. Estimating prevalence from the results of a screening test. Am J Epidemiol. 1978;107(1):71-6.
Lang Z, Reiczigel J (2014) Confidence limits for prevalence of disease adjusted for estimated sensitivity and specificity, Preventive Veterinary Medicine, 113, 13-22.