Table of Contents
Epidemiology Research International
Volume 2011, Article ID 608719, 5 pages
Research Article

Estimating Prevalence Using an Imperfect Test

1CHICAS, Faculty of Health and Medicine, Lancaster University, Lancaster LA1 4YA, UK
2Johns Hopkins University School of Public Health, Baltimore, MD 21205, USA

Received 18 June 2011; Accepted 2 August 2011

Academic Editor: Leo J. Schouten

Copyright © 2011 Peter J. Diggle. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The standard estimate of prevalence is the proportion of positive results obtained from the application of a diagnostic test to a random sample of individuals drawn from the population of interest. When the diagnostic test is imperfect, this estimate is biased. We give simple formulae, previously described by Greenland (1996) for correcting the bias and for calculating confidence intervals for the prevalence when the sensitivity and specificity of the test are known. We suggest a Bayesian method for constructing credible intervals for the prevalence when sensitivity and specificity are unknown. We provide R code to implement the method.