simuEpi: Simulate an epidemic following a SIR model

In thibautjombart/OutbreakTools: Basic Tools for the Analysis of Disease Outbreaks

Description

Simulate an epidemic following a SIR model, together with a transmission tree and a set of sequences consistent with the trajectory of the epidemic.

Usage

  simuEpi(N = 1000, D = 10, beta = 0.001, nu = 0.1, L = 1000, mu =
          0.001, plot=TRUE, makePhyloTree=FALSE)

Arguments

N	Size of the population
D	Duration of simulation
beta	Rate of infection
nu	Rate of recovery
L	Length of genetic sequences
mu	Probability of mutation per base per transmission event
plot	logical indicating whether or not to plot the SIR trajectory over time and save it in the output.
makePhyloTree	Logical; whether to create a neighbour-joining tree from the simulated sequences.

Value

A list containing the SIR dynamics ($dynamics), an obkData of the outbreak ($x), and an optional ggplot graphic ($plot).

Author(s)

Original version by Xavier Didelot and Caroline Colijn. Graphics modification by Thibaut Jombart.

Examples

## Not run: 
## Simulate an outbreak of 200 individuals over 20 time steps ##
set.seed(3)

x <- simuEpi(N = 200, D = 20, beta = 0.002, nu = 0.1, mu = 0.002)

## x is a list:
class(x)
names(x)

## x$dynamics contains demographic info
x$dynamics

## x$plot is a ggplot object
class(x$plot)
x$plot

## x$x is the obkData object
summary(x$x)
plotIndividualTimeline(x$x, colorBy="DateInfected")


## Same, with a phylogenetic tree
x <- simuEpi(N = 200, D = 20, beta = 0.002, nu = 0.1, mu = 0.002,
             plot=TRUE, makePhyloTree=TRUE)

plotggphy(x$x, ladderize=TRUE, show.tip=TRUE,
      branch.unit="year", tip.label.size=4)

## End(Not run)

thibautjombart/OutbreakTools documentation built on Oct. 26, 2019, 10:56 p.m.