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Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling

Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models h...

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Detalles Bibliográficos
Autores principales: Mao, Liang, Yang, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126515/
https://www.ncbi.nlm.nih.gov/pubmed/22154610
http://dx.doi.org/10.1016/j.socscimed.2011.10.012
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author Mao, Liang
Yang, Yan
author_facet Mao, Liang
Yang, Yan
author_sort Mao, Liang
collection PubMed
description Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. This article proposes a conceptual framework to fill this knowledge gap and illustrates the model establishment. The conceptual model consists of two networks and two diffusion processes. The two networks include: an infection network that transmits diseases and a communication network that channels inter-personal influence regarding preventive behavior. Both networks are composed of same individuals but different types of interactions. This article further introduces modeling approaches to formulize such a framework, including the individual-based modeling approach, network theory, disease transmission models and behavioral models. An illustrative model was implemented to simulate a coupled-diffusion process during an influenza epidemic. The simulation outcomes suggest that the transmission probability of a disease and the structure of infection network have profound effects on the dynamics of coupled-diffusion. The results imply that current models may underestimate disease transmissibility parameters, because human preventive behavior has not been considered. This issue calls for a new interdisciplinary study that incorporates theories from epidemiology, social science, behavioral science, and health psychology.
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spelling pubmed-71265152020-04-08 Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling Mao, Liang Yang, Yan Soc Sci Med Article Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. This article proposes a conceptual framework to fill this knowledge gap and illustrates the model establishment. The conceptual model consists of two networks and two diffusion processes. The two networks include: an infection network that transmits diseases and a communication network that channels inter-personal influence regarding preventive behavior. Both networks are composed of same individuals but different types of interactions. This article further introduces modeling approaches to formulize such a framework, including the individual-based modeling approach, network theory, disease transmission models and behavioral models. An illustrative model was implemented to simulate a coupled-diffusion process during an influenza epidemic. The simulation outcomes suggest that the transmission probability of a disease and the structure of infection network have profound effects on the dynamics of coupled-diffusion. The results imply that current models may underestimate disease transmissibility parameters, because human preventive behavior has not been considered. This issue calls for a new interdisciplinary study that incorporates theories from epidemiology, social science, behavioral science, and health psychology. Elsevier Ltd. 2012-01 2011-11-26 /pmc/articles/PMC7126515/ /pubmed/22154610 http://dx.doi.org/10.1016/j.socscimed.2011.10.012 Text en Copyright © 2011 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Mao, Liang
Yang, Yan
Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling
title Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling
title_full Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling
title_fullStr Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling
title_full_unstemmed Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling
title_short Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling
title_sort coupling infectious diseases, human preventive behavior, and networks – a conceptual framework for epidemic modeling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126515/
https://www.ncbi.nlm.nih.gov/pubmed/22154610
http://dx.doi.org/10.1016/j.socscimed.2011.10.012
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