epi.prev {epiR}R Documentation

Estimate true prevalence

Description

Computes the true prevalence of a disease in a population on the basis of an imperfect test.

Usage

epi.prev(pos, tested, se, sp, conf.level = 0.95)

Arguments

pos the number of positives.
tested the number tested.
se test sensitivity (0 - 1).
sp test specificity (0 - 1).
conf.level magnitude of the returned confidence interval. Must be a single number between 0 and 1.

Value

A list containing the following:

ap the point estimate of apparent prevalence, the standard error of the apparent prevalence, and the lower and upper bounds of the apparent prevalence.
tp the point estimate of the true prevalence, the standard error of the true prevalence, and the lower and upper bounds of the true prevalence.

Note

This function uses the apparent prevalence, test sensitivity and test specificity to estimate true prevalence (after Rogan and Gladen, 1978). The standard error of the Rogan Gladen true prevalence estimate is based on Abel (1993).

References

Abel U (1993). DieBewertung Diagnostischer Tests. hippkrates, Stuttgart.

Gardener IA, Greiner M (1999). Advanced Methods for Test Validation and Interpretation in Veterinary Medicince. Freie Universitat Berlin, ISBN 3-929619-22-9; 80 pp.

Rogan W, Gladen B (1978). Estimating prevalence from results of a screening test. American Journal of Epidemiology 107: 71 - 76.

Examples

## A simple random sample of 150 cows from a herd of 2560 is taken.
## Each cow is given a screening test for brucellosis which has a 
## sensitivity of 96% and a specificity of 89%. Of the 150 cows tested
## 23 were positive to the screening test. What is the estimated prevalence 
## of brucellosis in this herd (and its 95% confidence interval)?

epi.prev(pos = 23, tested = 150, se = 0.96, sp = 0.89, conf.level = 0.95)

## The estimated true prevalence of brucellosis in this herd is 5.1 cases per 
## 100 cows (95% CI 0 -- 12 cases per 100 cows).

[Package epiR version 0.9-15 Index]