rsu.sep.pass {epiR} | R Documentation |

Calculates the surveillance system (population-level) sensitivity for detection of disease for a passive surveillance system assuming comprehensive population coverage and sampling of clinical cases within diseased clusters.

rsu.sep.pass(N, n, step.p, pstar.c, p.inf.u, se.u)

`N` |
scalar or vector of length equal to the number of rows in |

`n` |
scalar or vector of length equal to the number of rows in |

`step.p` |
vector or matrix of detection probabilities (0 to 1) for each step in the detection process. If a vector each value represents a step probability for a single calculation. If a matrix, columns are step probabilities and rows are simulation iterations. |

`pstar.c` |
scalar (0 to 1) or vector of length equal to the number of rows in |

`p.inf.u` |
scalar (0 to 1) or vector of length equal to the number of rows in |

`se.u` |
scalar (0 to 1) or vector of length equal to the number of rows in |

A list comprised of two elements:

`se.p` |
scalar or vector, the estimated surveillance system (population-level) sensitivity of detection. |

`se.c` |
scalar or vector, the estimated cluster-level sensitivity of detection. |

If `step.p`

is a vector, scalars are returned. If `step.p`

is a matrix, values are vectors of length equal to the number of rows in `step.p`

.

Lyngstad T, Hellberg H, Viljugrein H, Bang Jensen B, Brun E, Sergeant E, Tavornpanich S (2016). Routine clinical inspections in Norwegian marine salmonid sites: A key role in surveillance for freedom from pathogenic viral haemorrhagic septicaemia (VHS). Preventive Veterinary Medicine 124: 85 - 95. DOI: 10.1016/j.prevetmed.2015.12.008.

## EXAMPLE 1: ## A passive surveillance system for disease X operates in your country. ## There are four steps to the diagnostic cascade with detection probabilities ## for each process of 0.10, 0.20, 0.90 and 0.99, respectively. Assuming the ## probability that a unit actually has disease if it is submitted for ## testing is 0.98, the sensitivity of the diagnostic test used at the unit ## level is 0.90, the population is comprised of 1000 clusters (herds), ## five animals from each cluster (herd) are tested and the cluster-level ## design prevalence is 0.01, what is the sensitivity of disease detection ## at the cluster (herd) and population level? rsu.sep.pass(N = 1000, n = 5, step.p = c(0.10,0.20,0.90,0.99), pstar.c = 0.01, p.inf.u = 0.98, se.u = 0.90) ## The sensitivity of disease detection at the cluster (herd) level is 0.018. ## The sensitivity of disease detection at the population level is 0.16.

[Package *epiR* version 2.0.31 Index]