episim {EpiLPS}

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 [e-mail]

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)