rsu.sep.rs {epiR} R Documentation

## Surveillance system sensitivity assuming representative sampling

### Description

Calculates the surveillance system (population-level) sensitivity for detection of disease assuming representative sampling, imperfect test sensitivity and perfect test specificity using the hypergeometric method if `N` is known and the binomial method if `N` is unknown.

### Usage

```rsu.sep.rs(N = NA, n, pstar, se.u = 1)
```

### Arguments

 `N` scalar integer or vector of integers the same length as `n`, representing the population size. Use `NA` if unknown. `n` scalar integer or vector of integers representing the number of units tested. `pstar` scalar numeric or vector of numbers the same length as `n` representing the design prevalence. See details, below. `se.u` scalar numeric or vector of numbers the same length as `n` representing the unit sensitivity.

### Value

A vector of surveillance system (population-level) sensitivity estimates.

### References

MacDiarmid S (1988). Future options for brucellosis surveillance in New Zealand beef herds. New Zealand Veterinary Journal 36: 39 - 42.

Martin S, Shoukri M, Thorburn M (1992). Evaluating the health status of herds based on tests applied to individuals. Preventive Veterinary Medicine 14: 33 - 43.

### Examples

```## EXAMPLE 1:
## Three hundred samples are to be tested from a population of animals to
## confirm the absence of a disease. The total size of the population is
## unknown. Assuming a design prevalence of 0.01 and a test with
## diagnostic sensitivity of 0.95 will be used what is the sensitivity of
## disease detection at the population level?

rsu.sep.rs(N = NA, n = 300, pstar = 0.01, se.u = 0.95)

## The sensitivity of disease detection at the population level is 0.943.

## EXAMPLE 2:
## Thirty animals from five herds ranging in size from 80 to 100 head are to be
## sampled to confirm the absence of a disease. Assuming a design prevalence
## of 0.01 and a test with diagnostic sensitivity of 0.95 will be used, what
## is the sensitivity of disease detection for each herd?

N <- seq(from = 80, to = 100, by = 5)
n <- rep(30, times = length(N))
rsu.sep.rs(N = N, n = n, pstar = 0.01, se.u = 0.95)

## The sensitivity of disease detection for each herd ranges from 0.28 to
## 0.36.

```

[Package epiR version 2.0.31 Index]