Protection Degree and Migration in the Stochastic SIRS Model: A Queueing System Perspective
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917097386278912 |
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| author | Li, Yuhan Zeng, Ziyan Feng, Minyu Kurths, Jürgen |
| author_facet | Li, Yuhan Zeng, Ziyan Feng, Minyu Kurths, Jürgen |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03159 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Protection Degree and Migration in the Stochastic SIRS Model: A Queueing System Perspective Li, Yuhan Zeng, Ziyan Feng, Minyu Kurths, Jürgen Social and Information Networks Systems and Control Physics and Society 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. |
| title | Protection Degree and Migration in the Stochastic SIRS Model: A Queueing System Perspective |
| topic | Social and Information Networks Systems and Control Physics and Society |
| url | https://arxiv.org/abs/2407.03159 |