In grattan/covidReff: Simulate Covid

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

library(dplyr)
devtools::load_all()

covidReff

The goal of covidReff is to simulate Covid outbreaks in a partially vaccinated population.

Installation

The development version from GitHub with:

# install.packages("remotes")
remotes::install_github("grattan/covidReff")

Usage

The simulate_covid() runs simulations of Covid spreading and returns a tibble with the results for each simulation (runid) on each day. Using the default settings:

sim_results <- simulate_covid()

The resulting tibble is:

glimpse(sim_results)

The key inputs of the simulate_covid() function -- among many -- are the reproduction value of the virus in a 'relaxed' Australian society, R, and the proportion of the whole population that are vaccinated, vaccination_levels.

sim_r8_50 <- simulate_covid(R = 8, 
                            vaccination_levels = .5)

The vaccination_levels is provided as either a single numeric for vaccination levels uniformly-distributed across age groups (as above), or you can provide a numeric vector of length 10 describing the vaccination rates for age groups 1-10, 11-20, 21-30, ..., 91-100.

sim_r4_50 <- simulate_covid(
  R = 4, 
  vaccination_levels = c(
    "0-10"  = 0.00,
    "11-20" = 0.40,
    "21-30" = 0.60,
    "31-40" = 0.60,
    "41-50" = 0.60,
    "51-60" = 0.70,
    "61-70" = 0.90,
    "71-80" = 0.90,
    "81-90" = 0.95,
    "91+"   = 0.95)
  )
glimpse(sim_r4_50)