This R code accompanies a The Conversation article on the effects of spatial and temporal physical distancing in reducing the rate of COVID-19 infection: 'Want to make social distancing even more effective? It’s about time (as well as space'
Authors:
For code queries, contact: Professor Corey J. A. Bradshaw, Global Ecology, College of Science and Engineering, GPO Box 2100, Flinders University, Adelaide, South Australia 5001, Australia
[email protected] +61 (0) 400 697 665
Cellular automaton model to investigate reductions in COVID-19 infection rate with spatial and temporal physical distancing
This R code produces an R×C matrix populated by N individuals.
For each cell, individual is resampled from a maximum of half the matrix dimension, with each movement conditioned a binomial probability set by the user.
The process can be run over t time steps and s iterations.
Note, there is no recovery component included.
The user can define two additional parameters:
- A reduction in movement probability (spatial distancing)
- A reduction of in exposure (temporal distancing)