episim {EpiLPS} | R Documentation |

## Simulation of an incidence time series

### Description

Based on a serial interval and a functional input for the reproduction number
over `T`

days, the routine generates an incidence time series following
a Poisson or negative binomial model. The link between the reproduction number
and the generated incidence data is governed by the renewal equation. The
baseline (mean) number of cases at day 1 is fixed at 10. The mean number of
cases for the remaining days of the epidemic are generated following
equation (2) of Azmon et al. (2013).

### Usage

```
episim(si, endepi = 50, Rpattern = 1, Rconst = 2.5,
dist = c("poiss", "negbin"), overdisp = 1, verbose = FALSE, plotsim = FALSE)
```

### Arguments

`si` |
The serial interval distribution. |

`endepi` |
The total number of days of the epidemic. |

`Rpattern` |
Different scenarios for the true underlying curve of Rt. Six scenarios are possible with 1,2,3,4,5,6. |

`Rconst` |
The constant value of R (if scenario 1 is selected), default is 2.5. |

`dist` |
The distribution from which to sample the incidence counts. Either Poisson (default) or negative binomial. |

`overdisp` |
Overdispersion parameter for the negative binomial setting. |

`verbose` |
Should metadata of the simulated epidemic be printed? |

`plotsim` |
Create a plot of the incidence time series, the true reproduction number curve and the serial interval. |

### Value

An object of class `episim`

consisting of a list with the
generated incidence time series, the mean vector of the Poisson/negative binomial
distribution, the true underlying R function for the data generating process and the
chosen serial interval distribution.

### Author(s)

Oswaldo Gressani oswaldo_gressani@hotmail.fr

### References

Azmon, A., Faes, C., Hens, N. (2014). On the estimation of the
reproduction number based on misreported epidemic data. *Statistics in
medicine*, **33**(7):1176-1192.

### Examples

```
si <- c(0.05, 0.05, 0.1, 0.1, 0.1, 0.1, 0.1, 0.05, 0.05, 0.1, 0.1, 0.1)
epidemic <- episim(si = si, Rpattern = 1)
```

*EpiLPS*version 1.3.0 Index]