epi.pooled {epiR}

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)

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).

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.

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.