epi.pooled: Estimate herd test characteristics when pooled sampling is...

In epiR: Tools for the Analysis of Epidemiological Data

Estimate herd test characteristics when pooled sampling is used

Description

We may wish to designate a group of individuals (e.g., a herd) as being either diseased or non-diseased on the basis of pooled samples. This function estimates sensitivity and specificity of this testing regime at the group (or herd) level.

Usage

epi.pooled(Se, Sp, P, m, r, dilution = FALSE)

Arguments

Se	a vector of length one defining the diagnostic sensitivity of the test at the individual sample level.
Sp	a vector of length one defining the diagnostic specificity of the test at the individual sample level.
P	scalar, the expected true prevalence of disease in the group (herd).
m	scalar, defining the number of individual samples to make up a pooled sample.
r	scalar, defining the number of pooled samples per group (or herd).
dilution	logical. If TRUE the function calculates a value for pooled diagnostic sensitivity dependent on the expected number of positives in the pool. If FALSE pooled diagnostic sensitivity is assumed to be the same as individual sample sensitivity.

Value

A list containing the following:

Se	the diagnostic sensitivity of the test at the individual sample level as entered by the user.
Sp	the diagnostic specificity of the test at the individual sample level as entered by the user.
PlSe	the diagnostic sensitivity of the test when samples are pooled.
PlSp	the diagnostic specificity of the test when samples are pooled.
HAPneg	the apparent prevalence in a disease negative herd.
HSe	the estimated group (herd) level sensitivity.
HSp	the estimated group (herd) level specificity.

References

Dohoo I, Martin W, Stryhn H (2014). Veterinary Epidemiologic Research. AVC Inc, Charlottetown, Prince Edward Island, Canada, pp. 126 - 128 .

Christensen J, Gardner IA (2000). Herd-level interpretation of test results for epidemiologic studies of animal diseases. Preventive Veterinary Medicine 45: 83 - 106.

Examples

## EXAMPLE 1:
## We want to test dairy herds for Johne's disease using faecal culture 
## which has a diagnostic sensitivity and specificity of 0.647 and 
## 0.981, respectively. Suppose faecal samples from five cows are pooled 
## and we collect six pooled samples per herd. What is the herd level 
## sensitivity and specificity using this approach assuming the true prevalence
## of disease is 0.12 and there are no dilution effects arising from pooling. 

epi.pooled(Se = 0.647, Sp = 0.981, P = 0.12, m = 5 , r = 6, dilution = FALSE)

## Herd level sensitivity is 0.927, herd level specificity is 0.562. 
## Sensitivity at the herd level is increased using the pooled sampling 
## approach. Herd level specificity is decreased.

## Re-calculate herd level sensitivity and specificity assuming there is a 
## dilution effect arising from pooling:

epi.pooled(Se = 0.647, Sp = 0.981, P = 0.12, m = 5 , r = 6, dilution = TRUE)

## Herd level sensitivity is 0.943, herd level specificity is 0.562. 

epiR documentation built on June 26, 2026, 9:07 a.m.