Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks

Handle URI:
http://hdl.handle.net/10754/623077
Title:
Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks
Authors:
Eksin, Ceyhun; Shamma, Jeff S. ( 0000-0001-5638-9551 ) ; Weitz, Joshua S.
Abstract:
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Eksin C, Shamma JS, Weitz JS (2017) Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks. Scientific Reports 7: 44122. Available: http://dx.doi.org/10.1038/srep44122.
Publisher:
Springer Nature
Journal:
Scientific Reports
Issue Date:
14-Mar-2017
DOI:
10.1038/srep44122
Type:
Article
ISSN:
2045-2322
Sponsors:
This work is supported by Army Research Office grant #W911NF-14-1-0402, and supported in part by KAUST. The authors thank K. Paarporn (Georgia Inst. Tech.), J. W. Glasser (Center for Disease Control (CDC)), and S. Riley (Imperial College London) for their comments.
Additional Links:
http://www.nature.com/articles/srep44122
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorEksin, Ceyhunen
dc.contributor.authorShamma, Jeff S.en
dc.contributor.authorWeitz, Joshua S.en
dc.date.accessioned2017-04-10T07:49:50Z-
dc.date.available2017-04-10T07:49:50Z-
dc.date.issued2017-03-14en
dc.identifier.citationEksin C, Shamma JS, Weitz JS (2017) Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks. Scientific Reports 7: 44122. Available: http://dx.doi.org/10.1038/srep44122.en
dc.identifier.issn2045-2322en
dc.identifier.doi10.1038/srep44122en
dc.identifier.urihttp://hdl.handle.net/10754/623077-
dc.description.abstractIndividuals 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.en
dc.description.sponsorshipThis work is supported by Army Research Office grant #W911NF-14-1-0402, and supported in part by KAUST. The authors thank K. Paarporn (Georgia Inst. Tech.), J. W. Glasser (Center for Disease Control (CDC)), and S. Riley (Imperial College London) for their comments.en
dc.publisherSpringer Natureen
dc.relation.urlhttp://www.nature.com/articles/srep44122en
dc.rightsThis 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/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleDisease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaksen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalScientific Reportsen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.en
dc.contributor.institutionSchool of Physics, Georgia Institute of Technology, Atlanta, GA, USA.en
kaust.authorShamma, Jeff S.en
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