Paper
22 April 2022 The application of Markov random walk model on the epidemic spread of Covid-19 via SEIR and SEIRS model
Wenbo Jin
Author Affiliations +
Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 1216327 (2022) https://doi.org/10.1117/12.2628089
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China
Abstract
Since the outbreak of the Covid-19 pandemic in 2020, most countries are still suffering from the virus, and human society has been greatly changed. As the new virus is highly contagious, many people are still infected with the virus every day, and even face death in serious cases. However, there are still a lot of people who do not realize the harm of the virus, in order to make people more intuitive feel the spread of the virus in a certain period, this paper will use two classic epidemiological mathematical models based on the Markov chain called SEIR and SEIRS model for simulating the virus spread in New York City in 180 days. In both models, there are four states: Susceptible, Exposed, Infected, and Recovered. At first, Markov chain was used to randomly generate a populous population, and only one person in the population was infected, and then the changes in the number of people in these four states were observed over time. In addition, by incorporating certain coefficients in the models into a formula, an index for measuring infectious diseases called Reproduction number (R0) will be obtained. The R0 of Covid-19 in New York City is about 5.93, much greater than 1. Indicating that on average one person can infect about six people, which is highly contagious, so measures need to be taken to reduce this number. Finally, the SEIRS model is more suitable by comparing these two models since people do get re-infected over time.
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Wenbo Jin "The application of Markov random walk model on the epidemic spread of Covid-19 via SEIR and SEIRS model", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 1216327 (22 April 2022); https://doi.org/10.1117/12.2628089
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KEYWORDS
Mathematical modeling

Ordinary differential equations

Computer simulations

Data modeling

Numerical simulations

Resistance

Stochastic processes

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