Game-theoretic modeling of collective decision making during epidemics
The spreading dynamics of an epidemic and the collective behavioral pattern of the population over which it spreads are deeply intertwined and the latter can critically shape the outcome of the former. Motivated by this, we design a parsimonious game-theoretic behavioral-epidemic model, in which an...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | English |
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AMER PHYSICAL SOC
2021
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/89031 |
| _version_ | 1848765143209476096 |
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| author | Ye, Mengbin Zino, L. Rizzo, A. Cao, M. |
| author_facet | Ye, Mengbin Zino, L. Rizzo, A. Cao, M. |
| author_sort | Ye, Mengbin |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The spreading dynamics of an epidemic and the collective behavioral pattern of the population over which it spreads are deeply intertwined and the latter can critically shape the outcome of the former. Motivated by this, we design a parsimonious game-theoretic behavioral-epidemic model, in which an interplay of realistic factors shapes the coevolution of individual decision making and epidemics on a network. Although such a coevolution is deeply intertwined in the real world, existing models schematize population behavior as instantaneously reactive, thus being unable to capture human behavior in the long term. Our paradigm offers a unified framework to model and predict complex emergent phenomena, including successful collective responses, periodic oscillations, and resurgent epidemic outbreaks. The framework also allows us to provide analytical insights on the epidemic process and to assess the effectiveness of different policy interventions on ensuring a collective response that successfully eradicates the outbreak. Two case studies, inspired by real-world diseases, are presented to illustrate the potentialities of the proposed model. |
| first_indexed | 2025-11-14T11:30:34Z |
| format | Journal Article |
| id | curtin-20.500.11937-89031 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:30:34Z |
| publishDate | 2021 |
| publisher | AMER PHYSICAL SOC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-890312022-08-17T04:15:40Z Game-theoretic modeling of collective decision making during epidemics Ye, Mengbin Zino, L. Rizzo, A. Cao, M. Science & Technology Physical Sciences Physics, Fluids & Plasmas Physics, Mathematical Physics SOCIAL-INFLUENCE DYNAMICS VACCINATION BEHAVIOR SPREAD IMITATION EVOLUTION NETWORKS COVID-19 The spreading dynamics of an epidemic and the collective behavioral pattern of the population over which it spreads are deeply intertwined and the latter can critically shape the outcome of the former. Motivated by this, we design a parsimonious game-theoretic behavioral-epidemic model, in which an interplay of realistic factors shapes the coevolution of individual decision making and epidemics on a network. Although such a coevolution is deeply intertwined in the real world, existing models schematize population behavior as instantaneously reactive, thus being unable to capture human behavior in the long term. Our paradigm offers a unified framework to model and predict complex emergent phenomena, including successful collective responses, periodic oscillations, and resurgent epidemic outbreaks. The framework also allows us to provide analytical insights on the epidemic process and to assess the effectiveness of different policy interventions on ensuring a collective response that successfully eradicates the outbreak. Two case studies, inspired by real-world diseases, are presented to illustrate the potentialities of the proposed model. 2021 Journal Article http://hdl.handle.net/20.500.11937/89031 10.1103/PhysRevE.104.024314 English AMER PHYSICAL SOC fulltext |
| spellingShingle | Science & Technology Physical Sciences Physics, Fluids & Plasmas Physics, Mathematical Physics SOCIAL-INFLUENCE DYNAMICS VACCINATION BEHAVIOR SPREAD IMITATION EVOLUTION NETWORKS COVID-19 Ye, Mengbin Zino, L. Rizzo, A. Cao, M. Game-theoretic modeling of collective decision making during epidemics |
| title | Game-theoretic modeling of collective decision making during epidemics |
| title_full | Game-theoretic modeling of collective decision making during epidemics |
| title_fullStr | Game-theoretic modeling of collective decision making during epidemics |
| title_full_unstemmed | Game-theoretic modeling of collective decision making during epidemics |
| title_short | Game-theoretic modeling of collective decision making during epidemics |
| title_sort | game-theoretic modeling of collective decision making during epidemics |
| topic | Science & Technology Physical Sciences Physics, Fluids & Plasmas Physics, Mathematical Physics SOCIAL-INFLUENCE DYNAMICS VACCINATION BEHAVIOR SPREAD IMITATION EVOLUTION NETWORKS COVID-19 |
| url | http://hdl.handle.net/20.500.11937/89031 |