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    Game-theoretic modeling of collective decision making during epidemics

    88855.pdf (1.033Mb)
    Access Status
    Open access
    Authors
    Ye, Mengbin
    Zino, L.
    Rizzo, A.
    Cao, M.
    Date
    2021
    Type
    Journal Article
    
    Metadata
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    Citation
    Ye, M. and Zino, L. and Rizzo, A. and Cao, M. 2021. Game-theoretic modeling of collective decision making during epidemics. Physical Review E. 104 (2): ARTN 024314.
    Source Title
    Physical Review E
    DOI
    10.1103/PhysRevE.104.024314
    ISSN
    2470-0045
    Faculty
    Faculty of Science and Engineering
    School
    School of Elec Eng, Comp and Math Sci (EECMS)
    Remarks

    Copyright © 2021 American Physical Society

    URI
    http://hdl.handle.net/20.500.11937/89031
    Collection
    • Curtin Research Publications
    Abstract

    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.

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