Protection Degree and Migration in the Stochastic SIRS Model: A Queueing System 
Perspective

Li, Yuhan; Zeng, Ziyan; Feng, Minyu; Kurths, Jürgen

doi:10.1109/TCSI.2021.3119978

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Protection Degree and Migration in the Stochastic SIRS Model: A Queueing System Perspective

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Li, Yuhan
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Zeng, Ziyan
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Feng, Minyu
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Kurths, Jürgen
Potsdam Institute for Climate Impact Research;

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Li, Y., Zeng, Z., Feng, M., Kurths, J. (2022): Protection Degree and Migration in the Stochastic SIRS Model: A Queueing System Perspective. - IEEE Transactions on Circuits and Systems I: Regular Papers, 69, 2, 771-783.
https://doi.org/10.1109/TCSI.2021.3119978

Cite as: https://publications.pik-potsdam.de/pubman/item/item_26572

Abstract

With the prevalence of COVID-19, the modeling of epidemic propagation and its analyses have played a significant role in controlling epidemics. However, individual behaviors, in particular the self-protection and migration, which have a strong influence on epidemic propagation, were always neglected in previous studies. In this paper, we mainly propose two models from the individual and population perspectives. In the first individual model, we introduce the individual protection degree that effectively suppresses the epidemic level as a stochastic variable to the SIRS model. In the alternative population model, an open Markov queueing network is constructed to investigate the individual number of each epidemic state, and we present an evolving population network via the migration of people. Besides, stochastic methods are applied to analyze both models. In various simulations, the infected probability, the number of individuals in each state and its limited distribution are demonstrated.