rsu.epinf {epiR} R Documentation

## Effective probability of disease

### Description

Calculates the effective probability of disease (adjusted design prevalence) for each risk group within a population.

### Usage

```rsu.epinf(pstar, rr, ppr)
```

### Arguments

 `pstar` scalar, the design prevalence. `rr` vector, defining the relative risk values for each strata in the population. `ppr` vector of length `rr` defining the population proportions in each strata.

### Value

A list of comprised of two elements:

 `epinf` a vector listing the effective probability of infection listed in order of `rr`. `adj.risk` a vector listing the adjusted risk values listed in order of `rr`.

### Examples

```## EXAMPLE 1:
## For a given disease of interest you believe that there is a 'high risk'
## and 'low risk' area in your country. The risk of disease in the high risk
## area compared with the low risk area is 5. A recent census shows that
## 10% of the population are resident in the high risk area and 90%
## are resident in the low risk area. You elect to set a design prevalence
## of 0.10.

## Calculate the effective probability of infection for each area.

rsu.epinf(pstar = 0.1, rr = c(5,1), ppr = c(0.10,0.90))

## The effective probabilities of infection for the high and low risk areas
## are 0.36 and 0.07, respectively.

## EXAMPLE 2:
## Re-calculate the effective probabilities of infection assuming there are
## 'high', 'medium' and 'low' risk areas. The risk of disease in the
## medium risk area compared with the low risk area is 3. Population
## proportions for each area are 0.10, 0.10 and 0.80, respectively.

rsu.epinf(pstar = 0.10, rr = c(5,3,1), ppr = c(0.10,0.10,0.80))

## The effective probabilities of infection for the high, medium and low
## risk areas are 0.31, 0.19 and 0.06, respectively.

```

[Package epiR version 2.0.38 Index]