episim {EpiLPS} | R Documentation |
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).
episim(si, endepi = 50, Rpattern = 1, Rconst = 2.5,
dist = c("poiss", "negbin"), overdisp = 1, verbose = FALSE, plotsim = FALSE)
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. |
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.
Oswaldo Gressani oswaldo_gressani@hotmail.fr
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.
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)