Modeling adaptive forward-looking behavior in epidemics on networks

Lorenzo Amir Nemati Fard, Alberto Bisin, Michele Starnini and Michele Tizzoni

Journal of Economic Behavior & Organization, 2025, vol. 232, issue C

Abstract: Incorporating decision-making dynamics during an outbreak poses a challenge for epidemiology, faced by several modeling approaches siloed by different disciplines. We propose an epi-economic model where high-frequency choices of individuals respond to the infection dynamics over heterogeneous networks. Maintaining a rational forward-looking component to individual choices, agents follow a behavioral rule-of-thumb in the face of limited perceived forecasting precision in a highly uncertain epidemic environment. We describe the resulting equilibrium behavior of the epidemic by analytical expressions depending on the epidemic conditions. We study existence and welfare of equilibrium, identifying a fundamental negative externality. We also sign analytically the effects of the behavioral rule-of-thumb at different phases of the epidemic and characterize some comparative statics. Through numerical simulations, we contrast different information structures: global awareness – where individuals only know the prevalence of the disease in the population – with local awareness, where individuals know the prevalence in their neighborhood. We show that agents’ behavioral response through forward-looking choice can flatten the epidemic curve, but local awareness, by triggering highly heterogeneous behavioral responses, more effectively curbs the disease compared to global awareness.

Keywords: Epidemiology; Forward-looking behavior; Networks (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:232:y:2025:i:c:s0167268125000344

DOI: 10.1016/j.jebo.2025.106914

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