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.

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

a)

b)

Instructions: Enter parameters in the red cells. Answers will appear in blue below.

Test validation

D_{V}+

Number of known infected cases in the validation study

T_{V}+ & D_{V}+

Number of positive test results among those cases

Sensitivity:

D_{V}−

Number of known non-infected controls in validation study

T_{V}− & D_{V}−

Number of negative test results among those cases

Specificity:

Prevalence

Sample size

Number of people tested in sample from target population.

T+

Number of positive test results in population.

P(T+)

Raw prevalence

CL

References:

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.