r2R0.Rd
The function r2R0
can be used to transform a growth rate into a
reproduction number estimate, given a generation time distribution. This uses
the approach described in Wallinga and Lipsitch (2007, Proc Roy Soc B
274:599–604) for empirical distributions. The function lm2R0_sample
generates a sample of R0 values from a loglinear regression of incidence
data stored in a lm
object.
r2R0(r, w, trunc = 1000) lm2R0_sample(x, w, n = 100, trunc = 1000)
r  A vector of growth rate values. 

w  The serial interval distribution, either provided as a

trunc  The number of time units (most often, days), used for truncating

x  A 
n  The number of draws of R0 values, defaulting to 100. 
It is assumed that the growth rate ('r') is measured in the same time unit as the serial interval ('w' is the SI distribution, starting at time 0).
## Ebola estimates of the SI distribution from the first 9 months of ## WestAfrican Ebola oubtreak mu < 15.3 # days sigma < 9.3 # days param < gamma_mucv2shapescale(mu, sigma / mu) if (require(distcrete)) { w < distcrete("gamma", interval = 1, shape = param$shape, scale = param$scale, w = 0) r2R0(c(1, 0.001, 0, 0.001, 1), w) ## Use simulated Ebola outbreak and 'incidence' to get a loglinear ## model of daily incidence. if (require(outbreaks) && require(incidence)) { i < incidence(ebola_sim$linelist$date_of_onset) plot(i) f < fit(i[1:100]) f plot(i[1:150], fit = f) R0 < lm2R0_sample(f$model, w) hist(R0, col = "grey", border = "white", main = "Distribution of R0") summary(R0) } }#>#>#>#> #> #> #>#> Warning: 22 dates with incidence of 0 ignored for fitting#> Min. 1st Qu. Median Mean 3rd Qu. Max. #> 1.182 1.261 1.290 1.288 1.318 1.424