epiR (version 2.0.78)

rsu.sep.rs2st: Surveillance system sensitivity assuming representative two-stage sampling

Description

Calculates the surveillance system sensitivity for detection of disease assuming two-stage sampling (sampling of clusters and sampling of units within clusters), imperfect test sensitivity and perfect test specificity.

Usage

rsu.sep.rs2st(H = NA, N = NA, n, pstar.c, pstar.u, se.u = 1)

Value

A list comprised of:

se.p

the surveillance system (population-level) sensitivity of detection.

se.c

the cluster-level sensitivity of detection.

se.u

the unit-level sensitivity of detection.

N

the number of units within each cluster, as entered by the user.

n

the number of units tested within each cluster, as entered by the user.

Arguments

H

scalar, integer representing the total number of clusters in the population. Use NA if unknown.

N

vector, integer representing the number of units within each cluster. Use NA if unknown.

n

vector, integer representing the number of units tested within each cluster.

pstar.c

scalar, numeric (0 to 1) representing the cluster-level design prevalence.

pstar.u

scalar, numeric (0 to 1) representing the unit-level design prevalence.

se.u

scalar, numeric (0 to 1), representing the sensitivity of the diagnostic test at the individual unit level.

Examples

## EXAMPLE 1:
## A study is to be conducted to confirm the absence of enzootic bovine 
## leukosis disease in your country. Four herds are to be sampled from a 
## population of 500 herds. There are 550, 250, 700 and 200 cows in each of 
## the four herds. From each of the four herds 30 animals are to be sampled. 
## The design prevalence for this study is set to 0.01 at the herd level 
## and if a herd is positive for leukosis the individual animal level 
## design prevalence is set to 0.10. Assuming a test with diagnostic 
## sensitivity of 0.98 will be used, what is the sensitivity of 
## disease detection at the population and cluster (herd) level?

rsu.sep.rs2st(H = 500, N = c(550,250,700,200), n = rep(30, times = 4), 
   pstar.c = 0.01, pstar.u = 0.10, se.u = 0.98)

## The population level sensitivity of detection is 0.037. The cluster level
## sensitivity of detection ranges from 0.950 to 0.958.