sim.epidemic {IDSpatialStats} | R Documentation |
Simulation of an epidemic in space and time
Description
A function which simulates the spatial spread of infections through time given the reproductive number (R
),
a function describing the spatial transmission kernel (trans.kern.func
), and the mean and standard deviation
of the generation time distribution (gen.t.mean
and gen.t.sd
) for the infecting pathogen. The function returns
the location (x
, y
) and time (t
) for each case of infection in the simulation.
Usage
sim.epidemic(
R,
gen.t.mean,
gen.t.sd,
trans.kern.func,
tot.generations = 10,
min.cases = 0,
max.try = 1000
)
Arguments
R |
a scalar or a vector of length |
gen.t.mean |
mean of generation time |
gen.t.sd |
standard deviation of the generation time (assumed to be normally distributed) |
trans.kern.func |
a function for the transmission kernel that takes |
tot.generations |
the total number of generations in the epidemic, where the index case (x,y,t = [0,0,0]) is considered generation zero (default = 10) |
min.cases |
the minimum number of cases in the epidemic (default = 0) |
max.try |
maximum number of tries to acheive the minimum number of cases (default = 1000) |
Value
a numerical matrix with three columns giving the coordinates x
and y
, and time t
of simulated cases
Author(s)
John Giles, Justin Lessler, and Henrik Salje
Examples
set.seed(1)
dist.func <- alist(n=1, a=1/100, rexp(n, a)) # Exponential transmission kernel with mean = sd = 100
# Simulate epidemic with constant R value
a <- sim.epidemic(R=1.5,
gen.t.mean=7,
gen.t.sd=2,
tot.generations=15,
min.cases=100,
trans.kern.func=dist.func)
sim.plot(a)
# Simulate an epidemic with variable R value
r1 <- 2
r2 <- 0.25
tg <- 25
R <- seq(r1, r2, (r2 -r1)/(tg - 1))
b <- sim.epidemic(R=R,
gen.t.mean=7,
gen.t.sd=2,
tot.generations=tg,
min.cases=100,
trans.kern.func=dist.func)
sim.plot(b)