Get the subpopulation level incident infections

Usage

subpop_inf_process(
  generate_inf_fxn,
  n_subpops,
  uot,
  ot,
  ht,
  unadj_r_site,
  initial_growth,
  initial_growth_prior_sd,
  i0_over_n,
  sd_i0_over_n,
  generation_interval,
  infection_feedback,
  infection_feedback_pmf,
  pop_fraction
)

Arguments

generate_inf_fxn: function indicating how to generate infections, This will typically take the generate_infections() function from the wwinference.stan model.
n_subpops: integer indicating the number of subpopulations
uot: integer indicating the days for exponential growth initialization to occur (referred to as unobserved time)
ot: integer indicating the number of days we will have observed data for in the calibration period
ht: integer indicating the time after the last observed time to forecast
unadj_r_site: n_subpop x n_weeks matrix of the unadjusted site level R(t)
initial_growth: float indicating the mean of the initial growth rate in the unobserved time
initial_growth_prior_sd: float indicating the standard deviation on the initial growth rate across subpopulations
i0_over_n: float indicating the mean of the initial per capita infections
sd_i0_over_n: float indicating the standard deviation of the log of the initial infections per capita across subpopulations
generation_interval: vector of simplex describing the probability of each time from infection to onwards transmission
infection_feedback: numeric indicating the strength of the infection feedback
infection_feedback_pmf: vector of simplex describing the delay from incident infections to feedback on incident infections
pop_fraction: vector of a simplex of length n_subpops, indicating the proportion of the global population that subpopulation represents

Value

A list containing 3 outputs: i_n: n_subpop X total days matrix of daily incident infections per capita in each subpopulation, r_site: adjusted subpopulation level R(t) estimate, i_n_global: vector of daily incident infections per capita in the global population