Simulate outbreak sizes

gistfile1.txt

## devtools::install_github("sbfnk/bpmodels")
library('bpmodels')
## 41 initial exposure events
n <- 41
## exposure events distributed over `nexp` days
nexp <- 26 ## 8 Dec - 2 Jan according to http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/337/1
## randomly sample exposure events
t0 <- sample(seq(1, 26), n, replace = TRUE)
## mean of serial interval distribution
mean_si <- 8.4 ## from Lispsitch et al. (2003)
## sd of serial interval distribution
sd_si <- 3.8 ## from Lispsitch et al. (2003)
## R0
R0 <- 2 ## to test
## k
k <- 0.16 ## from Lloyd-Smith (2005).
## end time
tf <- 37 ## 37 days from 8 Dec (see nexp)

## simulate chains
sim <- chain_sim(n, "nbinom", serial = function(x) rnorm(x, mean_si, sd_si),
                 mu = R0, size = k, t0 = t0, tf = tf)

## add reporting delays
times <- sim$time + 6.17 ## should use empirical distribution from linelist via the virological link
times <- times[times < tf]

## outbreak size
size <- length(times)