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It is critical to understand and model the behavior of individuals in apandemic, as well as identify effective ways to guide people's behavior inorder to better control the epidemic spread. However, current research fails toaccount for the impact of users' irrationality in decision-making, which is aprevalent factor in real-life scenarios. Additionally, existing disease controlmethods rely on measures such as mandatory isolation and assume thatindividuals will fully comply with these policies, which may not be true inreality. Thus, it is critical to find effective ways to guide people's behaviorduring an epidemic. To address these gaps, we propose a Prospect Theory-basedtheoretical framework to model individuals' decision-making process in anepidemic and analyze the impact of irrationality on the co-evolution of userbehavior and the epidemic. Our analysis shows that irrationality can leadindividuals to be more conservative when the risk of being infected is small,while irrationality tends to make users be more risk-seeking when the risk ofbeing infected is high. We then propose a behavior inducement algorithm toguide user behavior and control the spread of disease. Simulations and realuser tests validate our proposed model and analysis, and simulation resultsshow that our proposed behavior inducement algorithm can effectively guideusers' behavior.

Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control