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Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks
Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5349521/ https://www.ncbi.nlm.nih.gov/pubmed/28290504 http://dx.doi.org/10.1038/srep44122 |
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author | Eksin, Ceyhun Shamma, Jeff S. Weitz, Joshua S. |
author_facet | Eksin, Ceyhun Shamma, Jeff S. Weitz, Joshua S. |
author_sort | Eksin, Ceyhun |
collection | PubMed |
description | Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights. |
format | Online Article Text |
id | pubmed-5349521 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53495212017-03-17 Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks Eksin, Ceyhun Shamma, Jeff S. Weitz, Joshua S. Sci Rep Article Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights. Nature Publishing Group 2017-03-14 /pmc/articles/PMC5349521/ /pubmed/28290504 http://dx.doi.org/10.1038/srep44122 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Eksin, Ceyhun Shamma, Jeff S. Weitz, Joshua S. Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
title | Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
title_full | Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
title_fullStr | Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
title_full_unstemmed | Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
title_short | Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
title_sort | disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5349521/ https://www.ncbi.nlm.nih.gov/pubmed/28290504 http://dx.doi.org/10.1038/srep44122 |
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