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Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population

The susceptible-infected-susceptible epidemic model is analyzed through a degree-based mean-field approach. In this work, a mitigation factor is introduced in the probability of finding an infected individual following an edge. This modification simulates situations where the infected population red...

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Detalles Bibliográficos
Autores principales: Kim, K. M., Dias, C., Hase, M. O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198598/
http://dx.doi.org/10.1007/s13538-023-01312-x
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author Kim, K. M.
Dias, C.
Hase, M. O.
author_facet Kim, K. M.
Dias, C.
Hase, M. O.
author_sort Kim, K. M.
collection PubMed
description The susceptible-infected-susceptible epidemic model is analyzed through a degree-based mean-field approach. In this work, a mitigation factor is introduced in the probability of finding an infected individual following an edge. This modification simulates situations where the infected population reduces its participation in the dynamics of disease propagation, as may happen with the seclusion or hospitalization of infected individuals. A detailed investigation of this new model and its comparison to the original one (without the mitigation factor) was performed on the Barabási-Albert network, where some important results were analytically accessible.
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spelling pubmed-101985982023-05-23 Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population Kim, K. M. Dias, C. Hase, M. O. Braz J Phys Statistical The susceptible-infected-susceptible epidemic model is analyzed through a degree-based mean-field approach. In this work, a mitigation factor is introduced in the probability of finding an infected individual following an edge. This modification simulates situations where the infected population reduces its participation in the dynamics of disease propagation, as may happen with the seclusion or hospitalization of infected individuals. A detailed investigation of this new model and its comparison to the original one (without the mitigation factor) was performed on the Barabási-Albert network, where some important results were analytically accessible. Springer US 2023-05-19 2023 /pmc/articles/PMC10198598/ http://dx.doi.org/10.1007/s13538-023-01312-x Text en © The Author(s) under exclusive licence to Sociedade Brasileira de Física 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Statistical
Kim, K. M.
Dias, C.
Hase, M. O.
Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
title Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
title_full Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
title_fullStr Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
title_full_unstemmed Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
title_short Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
title_sort susceptible-infected-susceptible dynamics with mitigation in connection of infected population
topic Statistical
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198598/
http://dx.doi.org/10.1007/s13538-023-01312-x
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