discrete_SIR_simulator: Discrete in time SIR simulator

In OJWatson/paper: Demonstration of analysis associated to "paper outbreak" teaching practical

Description

discrete_SIR_simulator takes output of first_infection_list and outbreak_dataset_read and simulates a discrete time SIR epidemic time series using a user-provided R0, population size (N), number of initial seed infections (I) and time of seeding (seed.hour). The simulation uses a poisson distribrution to describe the number of secondary cases, the generation times and recovery times. The mean for the secondary cases is equal to R0, and the mean for the generation and recovery times is calculated from the user-provided first_infection_list and outbreak.dataset.

Usage

discrete_SIR_simulator(R0 = 1.8, N = NULL, I = 3, seed.hour = NULL,
  first_infection_list, outbreak.dataset, sampling = FALSE,
  exponential = FALSE)

Arguments

R0	Reproductive number. Default = 1.8
N	Total population size. If NULL (default) then the total population is the same as the provided datasets.
I	Number of initial seed infections. Default = 3
seed.hour	Hour at which seeding of epidemic begins. Default = 9
first_infection_list	Infection list outputted by first_infection_list
outbreak.dataset	Outbreak dataset outputted by outbreak_dataset_read
sampling	Boolean determining if recovery and generation times should be sampled from the observed or drawn fro a poisson with mean equal to mean of the observed. Default = FALSE (poisson draws used)
exponential	Boolean determining if infection is exponential or not. If FALSE (Default) then the number of secondary infections from an individual is takes into account S/N

OJWatson/paper documentation built on May 7, 2019, 8:33 p.m.