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A model for the co-evolution of dynamic social networks and infectious disease dynamics
Recent research shows an increasing interest in the interplay of social networks and infectious diseases. Many studies either neglect explicit changes in health behavior or consider networks to be static, despite empirical evidence that people seek to distance themselves from diseases in social netw...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495675/ https://www.ncbi.nlm.nih.gov/pubmed/34642614 http://dx.doi.org/10.1186/s40649-021-00098-9 |
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author | Nunner, Hendrik Buskens, Vincent Kretzschmar, Mirjam |
author_facet | Nunner, Hendrik Buskens, Vincent Kretzschmar, Mirjam |
author_sort | Nunner, Hendrik |
collection | PubMed |
description | Recent research shows an increasing interest in the interplay of social networks and infectious diseases. Many studies either neglect explicit changes in health behavior or consider networks to be static, despite empirical evidence that people seek to distance themselves from diseases in social networks. We propose an adaptable steppingstone model that integrates theories of social network formation from sociology, risk perception from health psychology, and infectious diseases from epidemiology. We argue that networking behavior in the context of infectious diseases can be described as a trade-off between the benefits, efforts, and potential harm a connection creates. Agent-based simulations of a specific model case show that: (i) high (perceived) health risks create strong social distancing, thus resulting in low epidemic sizes; (ii) small changes in health behavior can be decisive for whether the outbreak of a disease turns into an epidemic or not; (iii) high benefits for social connections create more ties per agent, providing large numbers of potential transmission routes and opportunities for the disease to travel faster, and (iv) higher costs of maintaining ties with infected others reduce final size of epidemics only when benefits of indirect ties are relatively low. These findings suggest a complex interplay between social network, health behavior, and infectious disease dynamics. Furthermore, they contribute to solving the issue that neglect of explicit health behavior in models of disease spread may create mismatches between observed transmissibility and epidemic sizes of model predictions. |
format | Online Article Text |
id | pubmed-8495675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-84956752021-10-08 A model for the co-evolution of dynamic social networks and infectious disease dynamics Nunner, Hendrik Buskens, Vincent Kretzschmar, Mirjam Comput Soc Netw Research Recent research shows an increasing interest in the interplay of social networks and infectious diseases. Many studies either neglect explicit changes in health behavior or consider networks to be static, despite empirical evidence that people seek to distance themselves from diseases in social networks. We propose an adaptable steppingstone model that integrates theories of social network formation from sociology, risk perception from health psychology, and infectious diseases from epidemiology. We argue that networking behavior in the context of infectious diseases can be described as a trade-off between the benefits, efforts, and potential harm a connection creates. Agent-based simulations of a specific model case show that: (i) high (perceived) health risks create strong social distancing, thus resulting in low epidemic sizes; (ii) small changes in health behavior can be decisive for whether the outbreak of a disease turns into an epidemic or not; (iii) high benefits for social connections create more ties per agent, providing large numbers of potential transmission routes and opportunities for the disease to travel faster, and (iv) higher costs of maintaining ties with infected others reduce final size of epidemics only when benefits of indirect ties are relatively low. These findings suggest a complex interplay between social network, health behavior, and infectious disease dynamics. Furthermore, they contribute to solving the issue that neglect of explicit health behavior in models of disease spread may create mismatches between observed transmissibility and epidemic sizes of model predictions. Springer International Publishing 2021-10-07 2021 /pmc/articles/PMC8495675/ /pubmed/34642614 http://dx.doi.org/10.1186/s40649-021-00098-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 | Research Nunner, Hendrik Buskens, Vincent Kretzschmar, Mirjam A model for the co-evolution of dynamic social networks and infectious disease dynamics |
title | A model for the co-evolution of dynamic social networks and infectious disease dynamics |
title_full | A model for the co-evolution of dynamic social networks and infectious disease dynamics |
title_fullStr | A model for the co-evolution of dynamic social networks and infectious disease dynamics |
title_full_unstemmed | A model for the co-evolution of dynamic social networks and infectious disease dynamics |
title_short | A model for the co-evolution of dynamic social networks and infectious disease dynamics |
title_sort | model for the co-evolution of dynamic social networks and infectious disease dynamics |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495675/ https://www.ncbi.nlm.nih.gov/pubmed/34642614 http://dx.doi.org/10.1186/s40649-021-00098-9 |
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