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Modeling Behavioral Response to Infectious Diseases Under Information Delay

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Abstract

We formulate and numerically solve a game-theoretic model of rational agents' self-protective actions in an epidemic game with information delay. We then compare our model simulation results with data collected from real human players in an online experiment conducted by Chen et al (2013). We find that, compared with game-theoretic agents, human players receive poorer endgame outcomes due to a lack of synchronization in their self-protective actions. In addition, human players' decisions are dependent on their infection history, and they are less responsive to changes in disease prevalence compared to game-theoretic agents. Our results suggest that human players in the epidemic game differ substantially from fully rational, forward-looking, strategic agents in terms of both player outcomes and decision-making mechanisms.

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  • Chen, Frederick & He, Haosen & Yu, Chu A.(Alex), 2024. "Modeling Behavioral Response to Infectious Diseases Under Information Delay," Working Papers 119, Wake Forest University, Economics Department.
    • Handle: RePEc:ris:wfuewp:0119
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    Keywords

    Game theory; Dynamic game; Economic epidemiology; Mathematical epidemiology; Epidemics; Information delay; Coninuous-state dynamic programming; Numerical simulation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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