Source code and secondary data of the stochastic process based COVID-19 simulation model [Image: see text]

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 proce...

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Detalles Bibliográficos
Autores principales: Manathunga, S.S., Abeyagunawardena, I.A., Dharmaratne, S.D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2022
Materias:
Original Software Publication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988451/
https://www.ncbi.nlm.nih.gov/pubmed/35411335
http://dx.doi.org/10.1016/j.simpa.2022.100284
Descripción
Sumario: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.

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