Generate an outbreak case count series defined by Reproduction number using a poisson model.

Generate an outbreak case count series defined by Reproduction number using a poisson model.

Usage

sim_poisson_Rt_model(
  changes = tibble::tibble(t = c(0, 40), rt = c(2.5, 0.8)),
  kappa = 1,
  max_time = 80,
  seed = Sys.time(),
  fn_Rt = cfg_step_fn(changes),
  fn_imports = ~ifelse(.x == 0, 30, 0),
  fn_ip = ~test_ip,
  time_unit = "1 day"
)

Arguments

changes

a dataframe holding change time points (t) and reproduction number (rt) columns

kappa

a dispersion parameter. 1 is no dispersion (compared to poisson), smaller values mean more dispersion.

max_time

the desired length of the time series,

seed

a random seed

fn_Rt

a function that takes input vector t and returns the instantaneous reproduction number at time t

fn_imports

a function that takes input vector t and returns the number of imported cases at times t.

fn_ip

a function that takes input vector t and returns an infectivity profile at times t.

time_unit

e.g. a daily or weekly time series: "1 day", "7 days"

Value

A dataframe containing the following columns:

• count (positive_integer) - Positive case counts associated with the specified timeframe

• time (ggoutbreak::time_period + group_unique) - A (usually complete) set of singular observations per unit time as a time_period

Ungrouped.

Examples

tmp = sim_poisson_Rt_model(kappa=1, seed=100, fn_imports = ~ ifelse(.x %in% c(0,50),100,0))

if (interactive()) {
  ggplot2::ggplot(tmp,ggplot2::aes(x=time,y=count))+ggplot2::geom_point()+
    ggplot2::geom_line()
}