biostudies-literatureUnknown12Manathunga SSThe 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.Software impacts100284https://www.ebi.ac.uk/biostudies/studies/S-EPMC8988451biostudies-literatureSource code and secondary data of the stochastic process based COVID-19 simulation model.PMC8988451Dharmaratne SDAbeyagunawardena IAManathunga SSfalseSource 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.2022-01-01T00:00:00Z2022 May2025-04-05T09:38:37.099Z2025-02-18T23:21:48.322ZS-EPMC89884513541133510.1016/j.simpa.2022.100284