epiR (version 2.0.76)

epi.pooled: 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)

Value

A list containing the following:

HAPneg

the apparent prevalence in a disease negative herd.

HSe

the estimated group (herd) level sensitivity.

HSp

the estimated group (herd) level specificity.

Arguments

se

a vector of length one defining the sensitivity of the individual test used.

sp

a vector of length one defining the specificity of the individual test used.

P

scalar, defining the estimated true prevalence.

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).

References

Dohoo I, Martin W, Stryhn H (2003). Veterinary Epidemiologic Research. AVC Inc, Charlottetown, Prince Edward Island, Canada, pp. 115 - 117 .

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 sensitivity and specificity of 0.647 and 0.981, respectively. 
## Suppose we pool faecal samples from five cows together and collect six 
## pooled samples per herd. What is the herd level sensitivity and specificity 
## based on this approach (assuming homogenous mixing)? 

epi.pooled(se = 0.647, sp = 0.981, P = 0.12, m = 5 , r = 6)

## 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.