A survey on Lyapunov functions for epidemic compartmental models

In this survey, we propose an overview on Lyapunov functions for a variety of compartmental models in epidemiology. We exhibit the most widely employed functions, and provide a commentary on their use. Our aim is to provide a comprehensive starting point to readers who are attempting to prove global...

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Detalles Bibliográficos
Autores principales: Cangiotti, Nicolò, Capolli, Marco, Sensi, Mattia, Sottile, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10242238/
https://www.ncbi.nlm.nih.gov/pubmed/37360758
http://dx.doi.org/10.1007/s40574-023-00368-6
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author Cangiotti, Nicolò
Capolli, Marco
Sensi, Mattia
Sottile, Sara
author_facet Cangiotti, Nicolò
Capolli, Marco
Sensi, Mattia
Sottile, Sara
author_sort Cangiotti, Nicolò
collection PubMed
description In this survey, we propose an overview on Lyapunov functions for a variety of compartmental models in epidemiology. We exhibit the most widely employed functions, and provide a commentary on their use. Our aim is to provide a comprehensive starting point to readers who are attempting to prove global stability of systems of ODEs. The focus is on mathematical epidemiology, however some of the functions and strategies presented in this paper can be adapted to a wider variety of models, such as prey–predator or rumor spreading.
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spelling pubmed-102422382023-06-07 A survey on Lyapunov functions for epidemic compartmental models Cangiotti, Nicolò Capolli, Marco Sensi, Mattia Sottile, Sara Boll Unione Mat Ital (2008) Article In this survey, we propose an overview on Lyapunov functions for a variety of compartmental models in epidemiology. We exhibit the most widely employed functions, and provide a commentary on their use. Our aim is to provide a comprehensive starting point to readers who are attempting to prove global stability of systems of ODEs. The focus is on mathematical epidemiology, however some of the functions and strategies presented in this paper can be adapted to a wider variety of models, such as prey–predator or rumor spreading. Springer International Publishing 2023-06-06 /pmc/articles/PMC10242238/ /pubmed/37360758 http://dx.doi.org/10.1007/s40574-023-00368-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Cangiotti, Nicolò
Capolli, Marco
Sensi, Mattia
Sottile, Sara
A survey on Lyapunov functions for epidemic compartmental models
title A survey on Lyapunov functions for epidemic compartmental models
title_full A survey on Lyapunov functions for epidemic compartmental models
title_fullStr A survey on Lyapunov functions for epidemic compartmental models
title_full_unstemmed A survey on Lyapunov functions for epidemic compartmental models
title_short A survey on Lyapunov functions for epidemic compartmental models
title_sort survey on lyapunov functions for epidemic compartmental models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10242238/
https://www.ncbi.nlm.nih.gov/pubmed/37360758
http://dx.doi.org/10.1007/s40574-023-00368-6
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