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Coupling Epidemiological Models with Social Dynamics

In this work we study a Susceptible-Infected-Susceptible model coupled with a continuous opinion dynamics model. We assume that each individual can take measures to reduce the probability of contagion, and the level of effort each agent applies can change due to social interactions. We propose simpl...

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Detalles Bibliográficos
Autores principales: Giambiagi Ferrari, Carlo, Pinasco, Juan Pablo, Saintier, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130810/
https://www.ncbi.nlm.nih.gov/pubmed/34008047
http://dx.doi.org/10.1007/s11538-021-00910-7
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author Giambiagi Ferrari, Carlo
Pinasco, Juan Pablo
Saintier, Nicolas
author_facet Giambiagi Ferrari, Carlo
Pinasco, Juan Pablo
Saintier, Nicolas
author_sort Giambiagi Ferrari, Carlo
collection PubMed
description In this work we study a Susceptible-Infected-Susceptible model coupled with a continuous opinion dynamics model. We assume that each individual can take measures to reduce the probability of contagion, and the level of effort each agent applies can change due to social interactions. We propose simple rules to model the propagation of behaviors that modify the level of effort, and analyze their impact on the dynamics of the disease. We derive a two dimensional set of ordinary differential equations describing the dynamic of the proportion of the number of infected individuals and the mean value of the effort parameter, and analyze the equilibria of the system. The stability of the endemic phase and disease free equilibria depends only on the mean value of the levels of efforts, and not on the initial distribution of levels of effort.
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spelling pubmed-81308102021-05-19 Coupling Epidemiological Models with Social Dynamics Giambiagi Ferrari, Carlo Pinasco, Juan Pablo Saintier, Nicolas Bull Math Biol Original Article In this work we study a Susceptible-Infected-Susceptible model coupled with a continuous opinion dynamics model. We assume that each individual can take measures to reduce the probability of contagion, and the level of effort each agent applies can change due to social interactions. We propose simple rules to model the propagation of behaviors that modify the level of effort, and analyze their impact on the dynamics of the disease. We derive a two dimensional set of ordinary differential equations describing the dynamic of the proportion of the number of infected individuals and the mean value of the effort parameter, and analyze the equilibria of the system. The stability of the endemic phase and disease free equilibria depends only on the mean value of the levels of efforts, and not on the initial distribution of levels of effort. Springer US 2021-05-18 2021 /pmc/articles/PMC8130810/ /pubmed/34008047 http://dx.doi.org/10.1007/s11538-021-00910-7 Text en © The Author(s), under exclusive licence to Society for Mathematical Biology 2021 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 Original Article
Giambiagi Ferrari, Carlo
Pinasco, Juan Pablo
Saintier, Nicolas
Coupling Epidemiological Models with Social Dynamics
title Coupling Epidemiological Models with Social Dynamics
title_full Coupling Epidemiological Models with Social Dynamics
title_fullStr Coupling Epidemiological Models with Social Dynamics
title_full_unstemmed Coupling Epidemiological Models with Social Dynamics
title_short Coupling Epidemiological Models with Social Dynamics
title_sort coupling epidemiological models with social dynamics
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130810/
https://www.ncbi.nlm.nih.gov/pubmed/34008047
http://dx.doi.org/10.1007/s11538-021-00910-7
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