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

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

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 Urheber:
Li, Yuhan1, Autor
Zeng, Ziyan1, Autor
Feng, Minyu1, Autor
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: 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.

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Sprache(n): eng - Englisch
 Datum: 2021-10-192022-02
 Publikationsstatus: Final veröffentlicht
 Seiten: 13
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1109/TCSI.2021.3119978
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Health
Research topic keyword: Complex Networks
 Art des Abschluß: -

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Titel: IEEE Transactions on Circuits and Systems I: Regular Papers
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 69 (2) Artikelnummer: - Start- / Endseite: 771 - 783 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/transactions-circuits-systems-regular-papers
Publisher: Institute of Electrical and Electronics Engineers (IEEE)