rsu.pstar {epiR} | R Documentation |
Calculates design prevalence required for given sample size and desired surveillance system (population-level) sensitivity, assuming representative sampling, imperfect test sensitivity and perfect test specificity.
rsu.pstar(N = NA, n, se.p, se.u)
N |
scalar or vector, integer representing the population size. Use |
n |
scalar or vector, integer representing the number of units sampled. |
se.p |
scalar or vector of the same length as |
se.u |
scalar or vector of the same length as |
A vector of design prevalence estimates.
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.
## EXAMPLE 1: ## In a study to provide evidence that your country is free of a given disease ## a total of 280 individuals are sampled. Assume a desired surveillance system ## sensitivity of 0.95 and an individual unit diagnostic sensitivity of 0.98. ## If all unit tests return a negative result, what is the maximum prevalence ## if disease is actually present in the population (i.e. what is the design ## prevalence)? rsu.pstar(N = NA, n = 280, se.p = 0.95, se.u = 0.98) ## If 280 individuals are sampled and tested and each returns a negative test ## result the maximum prevalence (if disease is actually present in the ## population) is 0.011. ## EXAMPLE 2: ## In a study to provide evidence disease freedom a total of 30 individuals ## are sampled from a set of cattle herds. Assume cattle herds in the study ## region range from 100 to 5000 cows. As above, assume a desired surveillance ## system sensitivity of 0.95 and an individuals unit diagnostic sensitivity ## of 0.98. If all 30 unit tests return a negative result, what is the expected ## design prevalence for each herd? round(rsu.pstar(N = c(100, 500, 1000, 5000), n = 30, se.p = 0.95, se.u = 0.98), digits = 3) ## The expected herd level design prevalence ranges from 0.086 (for a 100 ## cow herd) to 0.102 (for a 5000 cow herd).