感染症と治療ジャーナル

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Markovian Structures in Modelling SARS-COV-2

Elvis Han Cui, Weng Kee Wong

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.