Source code and secondary data of the stochastic process based COVID-19 simulation model

The novel coronavirus disease (COVID-19) culminated in a pandemic with many countries affected in varying stages. We aimed to develop a simulation environment for COVID-19 spread, taking environmental and social factors into account. This program consists of three main components; a stochastic process-based model for simulating epidemics, a basic reproduction number estimation unit and a graphics generator. The model can take a variety of environmental factors as input and simulate expected behaviours of the infection spread, enabling policymakers and the scientific community to test the effects of different mitigation strategies in a sandbox. •R language version 4.1.2 was utilized to write the source code for a stochastic process-based model for COVID-19 simulations, which has the ability to generate relevant data tables, figures and animations representing spread of COVID-19.•This source code can be used to analyse the spread of COVID-19 and COVID-19 like infections for all countries taking into account the differences in the diverse array of variables contributing to the spread.•This paper described the source code utilized in detail, with the aim of making this code widely available for policy making, research and learning.