incubsim: Simulation of incubation times

In EpiLPS: A Fast and Flexible Bayesian Tool for Estimating Epidemiological Parameters

Simulation of incubation times

Description

This routine simulates symptom onset times, generation times and left and right bounds of infecting exposure windows for source-recipient pairs based on a given incubation distribution and a generation time distribution. The generation time distribution is assumed to be a Weibull with shape 2.826 and scale 5.665 (Ferretti et al. 2020). The incubation distribution can be chosen by the user among:

• A LogNormal distribution with a mean of 5.5 days and standard deviation of 2.1 days (Ferretti et al. 2020).

• A Weibull distribution (shape-scale parameterization) with a mean of 6.4 days and standard deviation of 2.3 days (Backer et al. 2020).

• An artificial bimodal distribution constructed from a mixture of two Weibull distributions.

• A Gamma distribution (shape-rate parameterization) with a mean of 3.8 days and standard deviation of 2.9 days (Donnelly et al. 2003).

Usage

incubsim(incubdist = c("LogNormal","Weibull","MixWeibull", "Gamma"), coarseness = 1,
 n = 100, tmax = 20, tgridlen = 500, plotsim = FALSE)

Arguments

incubdist	The distribution of the incubation period.
coarseness	The average coarseness of the data. Default is 1 day.
n	The sample size.
tmax	The upper bound on which to evaluate the incubdist density.
tgridlen	The number of grid points on which to evaluate the density.
plotsim	Graphical visualization of the simulated data?

Value

A list including (among others) the left and right bounds of the incubation period.

Author(s)

Oswaldo Gressani [e-mail]

References

Ferretti, L., Wymant, C., Kendall, et al. (2020). Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science, 368(6491), eabb6936.

Backer, J. A., Klinkenberg, D., & Wallinga, J. (2020). Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020. Eurosurveillance, 25(5), 2000062.

Donnelly, C. A., Ghani, A. C., Leung, G. M., et al. (2003). Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong. The Lancet, 361(9371), 1761-1766.

Examples

simdat <- incubsim(n = 50) # Simulation of incubation times for 50 cases.
simdat$Dobsincub           # Left and right bounds of incubation period.

EpiLPS documentation built on May 29, 2024, 9:40 a.m.