Markovian Structures in Modelling SARS-COV-2
Received Date: Sep 29, 2022 / Published Date: Oct 31, 2022
Abstract
The aim of this paper is to model SARS-CoV-2 based on Markov chains. First, we introduce basic concepts of Markov chains with examples from different disciplines. Second, we use different types of Markov chains to model SARS-CoV-2, including confirmed cases, death and recovered cases and forecasting future confirmed cases. Third, we give conclusions based on these models and ideas for future work. Markov chains were found to be convenient and userful for simulation of the SARS-CoV-2 transmission dynamics while enabling detailed exploration under assumption of conditional independence. Nevertheless, there are also possibilities for extension of discrete time model to continuous time and consideration of spatial distribution of SARS-CoV-2.
Keywords: SARS-CoV-2, Markov chains, SEIRD model, Simulation
Citation: Cui EH, Wong WK (2022) Markovian Structures in Modelling SARS- COV-2. J Infect Dis Ther 10: 517. Doi: 10.4172/2332-0877.1000517
Copyright: © 2022 Cui EH, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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