In COVID-19-Modelling/BassSIR: Infectious disease modelling with Bass-SIR model

knitr::opts_chunk$set(echo = TRUE)

Before scenario analysis: loading package, model fitting, simulate a baseline case

library(BassSIR)
cases <- as_bass_data(n_covid19$Hubei, id = "Hubei")
est <- BassSIR::fit(cases, r_rec = 1/22.2, r_death = 1/22.3, type = "BassSIR")
sim <- simulate(est, nsim = 1000)

Setup scenario

Example case: Absolute lockdown $\kappa = 0 $

Scenario are set as function which modify the simulation parameters

zero_kappa <- function(pars) {
  pars$kappa <- rep(0, length(pars$kappa))
  return(pars)
}

Simulation from the estimated model

lockdown <- run_scenario(sim, zero_kappa)

Comparing different scenarios

compare_scenarios will output two group of time-series

Trajectories The trends of simulations of each variable
Change Calculate the value changes from the baseline case

cp <- compare_scenarios(sim, Lockdown = lockdown, fn_change = "Yt")

library(ggplot2)

ggplot(data = cp$Trajectories$I, aes(x = Time, y = mean, colour = Scenario)) +
  geom_ribbon(aes(ymin = lower, ymax = upper, fill = Scenario), alpha = 0.2) +
  geom_line()