Optimal strategies for vaccination and social distancing in a game-theoretic epidemiologic model
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, W. | - |
dc.contributor.author | Shim, E. | - |
dc.date.available | 2020-09-09T06:05:04Z | - |
dc.date.created | 2020-09-05 | - |
dc.date.issued | 2020-11 | - |
dc.identifier.issn | 0022-5193 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/38595 | - |
dc.description.abstract | For various infectious diseases, vaccination has become a major intervention strategy. However, the importance of social distancing has recently been highlighted during the ongoing COVID-19 pandemic. In the absence of vaccination, or when vaccine efficacy is poor, social distancing may help to curb the spread of new virus strains. However, both vaccination and social distancing are associated with various costs. It is critical to consider these costs in addition to the benefits of these strategies when determining the optimal rates of application of control strategies. We developed a game-theoretic epidemiological model that considers vaccination and social distancing under the assumption that individuals pursue the maximization of payoffs. By using this model, we identified the individually optimal strategy based on the Nash strategy when both strategies are available and when only one strategy is available. Furthermore, we determined the relative costs of control strategies at which individuals preferentially adopt vaccination over social distancing (or vice versa). © 2020 Elsevier Ltd | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Academic Press | - |
dc.relation.isPartOf | Journal of Theoretical Biology | - |
dc.title | Optimal strategies for vaccination and social distancing in a game-theoretic epidemiologic model | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.jtbi.2020.110422 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | Journal of Theoretical Biology, v.505 | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000599769200007 | - |
dc.identifier.scopusid | 2-s2.0-85088953621 | - |
dc.citation.title | Journal of Theoretical Biology | - |
dc.citation.volume | 505 | - |
dc.contributor.affiliatedAuthor | Shim, E. | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.subject.keywordAuthor | Game theory | - |
dc.subject.keywordAuthor | Infectious disease | - |
dc.subject.keywordAuthor | Nash | - |
dc.subject.keywordAuthor | Social-distancing | - |
dc.subject.keywordAuthor | Vaccine | - |
dc.subject.keywordPlus | COVID-19 | - |
dc.subject.keywordPlus | disease control | - |
dc.subject.keywordPlus | epidemiology | - |
dc.subject.keywordPlus | game theory | - |
dc.subject.keywordPlus | infectious disease | - |
dc.subject.keywordPlus | optimization | - |
dc.subject.keywordPlus | strategic approach | - |
dc.subject.keywordPlus | vaccination | - |
dc.subject.keywordPlus | Article | - |
dc.subject.keywordPlus | control strategy | - |
dc.subject.keywordPlus | endemic disease | - |
dc.subject.keywordPlus | epidemiological data | - |
dc.subject.keywordPlus | game | - |
dc.subject.keywordPlus | human | - |
dc.subject.keywordPlus | infection prevention | - |
dc.subject.keywordPlus | mathematical model | - |
dc.subject.keywordPlus | model | - |
dc.subject.keywordPlus | priority journal | - |
dc.subject.keywordPlus | social distance | - |
dc.subject.keywordPlus | strategic planning | - |
dc.subject.keywordPlus | vaccination | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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