R0 (version 1.2-10)

generation.time: Generation Time distribution

Description

Create an object of class GT representing a discretized Generation Time distribution.

Usage

generation.time(type = c("empirical", 
    "gamma", "weibull", 
    "lognormal"), val = NULL, 
    truncate = NULL, 
    step = 1, first.half = TRUE, 
    p0 = TRUE)

Value

A list with components:

GT

The probabilities for each time unit, starting at time 0.

time

The time at which probabilities are calculated.

mean

The mean of the discretized GT.

sd

The standard deviation of the discretized GT.

Arguments

type

Type of distribution.

val

Vector of values used for the empirical distribution, or c(mean, sd) if parametric.

truncate

Maximum extent of the GT distribution.

step

Time step used in discretization.

first.half

First probability computed on half period.

p0

Is probability on day 0 0

Author

Pierre-Yves Boelle, Thomas Obadia

Details

How the GT is discretized may have some impact on the shape of the distribution. For example, the distribution may be discretized in intervals of 1 time step starting at time 0, i.e. [0,1), [1,2), and so on. Or it may be discretized as [0,0.5), [0.5, 1.5), ... (the default).

If the GT is discretized from a given continuous distribution, the expected duration of the Generation Time will be less than the nominal, it will be in better agreement in the second discretization.

If p0 is TRUE (default) then the generation time distribution is set to 0 for day 0.

If no truncation is provided, the distribution will be truncated at 99.99 percent probability.

Examples

#Loading package
library(R0)

# GT for children at house(from Cauchemez PNAS 2011)

GT.chld.hsld1<-generation.time("empirical", c(0,0.25,0.2,0.15,0.1,0.09,0.05,0.01))
plot(GT.chld.hsld1, col="green")
GT.chld.hsld1
# Discretized Generation Time distribution
# mean: 2.729412 , sd: 1.611636 
# [1] 0.00000000 0.29411765 0.23529412 0.17647059 0.11764706 0.10588235 0.05882353
# [8] 0.01176471

GT.chld.hsld2<-generation.time("gamma", c(2.45, 1.38))
GT.chld.hsld2
# Discretized Generation Time distribution
# mean: 2.504038 , sd: 1.372760
# [1] 0.0000000000 0.2553188589 0.3247178420 0.2199060781 0.1144367560
# [6] 0.0515687896 0.0212246257 0.0082077973 0.0030329325 0.0010825594
#[11] 0.0003760069 0.0001277537


# GT for school & community
GTs1<-generation.time("empirical", c(0,0.95,0.05))
plot(GTs1, col='blue')


plot(GT.chld.hsld1, ylim=c(0,0.5), col="red")
par(new=TRUE)
plot(GT.chld.hsld2, xlim=c(0,7), ylim=c(0,0.5), col="black")