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Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes

The effectiveness of a mass vaccination program can engender its own undoing if individuals choose to not get vaccinated believing that they are already protected by herd immunity. This would appear to be the optimal decision for an individual, based on a strategic appraisal of her costs and benefit...

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Autores principales: Sharma, Anupama, Menon, Shakti N., Sasidevan, V., Sinha, Sitabhra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532839/
https://www.ncbi.nlm.nih.gov/pubmed/31120877
http://dx.doi.org/10.1371/journal.pcbi.1006977
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author Sharma, Anupama
Menon, Shakti N.
Sasidevan, V.
Sinha, Sitabhra
author_facet Sharma, Anupama
Menon, Shakti N.
Sasidevan, V.
Sinha, Sitabhra
author_sort Sharma, Anupama
collection PubMed
description The effectiveness of a mass vaccination program can engender its own undoing if individuals choose to not get vaccinated believing that they are already protected by herd immunity. This would appear to be the optimal decision for an individual, based on a strategic appraisal of her costs and benefits, even though she would be vulnerable during subsequent outbreaks if the majority of the population argues in this manner. We investigate how voluntary vaccination can nevertheless emerge in a social network of rational agents, who make informed decisions whether to be vaccinated, integrated with a model of epidemic dynamics. The information available to each agent includes the prevalence of the disease in their local network neighborhood and/or globally in the population, as well as the fraction of their neighbors that are protected against the disease. Crucially, the payoffs governing the decision of agents vary with disease prevalence, resulting in the vaccine uptake behavior changing in response to contagion spreading. The collective behavior of the agents responding to local prevalence can lead to a significant reduction in the final epidemic size, particularly for less contagious diseases having low basic reproduction number [Image: see text] . Near the epidemic threshold ([Image: see text] ) the use of local prevalence information can result in divergent responses in the final vaccine coverage. Our results suggest that heterogeneity in the risk perception resulting from the spatio-temporal evolution of an epidemic differentially affects agents’ payoffs, which is a critical determinant of the success of voluntary vaccination schemes.
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spelling pubmed-65328392019-06-05 Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes Sharma, Anupama Menon, Shakti N. Sasidevan, V. Sinha, Sitabhra PLoS Comput Biol Research Article The effectiveness of a mass vaccination program can engender its own undoing if individuals choose to not get vaccinated believing that they are already protected by herd immunity. This would appear to be the optimal decision for an individual, based on a strategic appraisal of her costs and benefits, even though she would be vulnerable during subsequent outbreaks if the majority of the population argues in this manner. We investigate how voluntary vaccination can nevertheless emerge in a social network of rational agents, who make informed decisions whether to be vaccinated, integrated with a model of epidemic dynamics. The information available to each agent includes the prevalence of the disease in their local network neighborhood and/or globally in the population, as well as the fraction of their neighbors that are protected against the disease. Crucially, the payoffs governing the decision of agents vary with disease prevalence, resulting in the vaccine uptake behavior changing in response to contagion spreading. The collective behavior of the agents responding to local prevalence can lead to a significant reduction in the final epidemic size, particularly for less contagious diseases having low basic reproduction number [Image: see text] . Near the epidemic threshold ([Image: see text] ) the use of local prevalence information can result in divergent responses in the final vaccine coverage. Our results suggest that heterogeneity in the risk perception resulting from the spatio-temporal evolution of an epidemic differentially affects agents’ payoffs, which is a critical determinant of the success of voluntary vaccination schemes. Public Library of Science 2019-05-23 /pmc/articles/PMC6532839/ /pubmed/31120877 http://dx.doi.org/10.1371/journal.pcbi.1006977 Text en © 2019 Sharma et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sharma, Anupama
Menon, Shakti N.
Sasidevan, V.
Sinha, Sitabhra
Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
title Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
title_full Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
title_fullStr Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
title_full_unstemmed Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
title_short Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
title_sort epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532839/
https://www.ncbi.nlm.nih.gov/pubmed/31120877
http://dx.doi.org/10.1371/journal.pcbi.1006977
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