Behavioral patterns and mean-field games in epidemiological models
Finnegan Buckley, Alexander Vladimirsky

TL;DR
This paper develops a novel mean-field game model for epidemiology that incorporates diverse behavioral patterns and switching behaviors, providing insights into how these factors influence disease spread and resource strain.
Contribution
It introduces a new mean-field game framework for epidemiological modeling that accounts for rational and non-rational behaviors and their switches, bridging epidemiology and game theory.
Findings
Behavioral diversity affects disease dynamics significantly.
Switching behaviors increase the impact of infectious diseases.
Model simulations highlight the importance of behavioral patterns in epidemic outcomes.
Abstract
We introduce a new type of Mean Field Game epidemiological models, in which subpopulations have different behavioral patterns: some are viewed as "highly rational" (choosing Nash-equilibrium long-term strategies) while others follow pre-specified "non-rational" patterns (e.g., either sticking to their usual habits or trying to mimic those around them). Our model also allows for occasional behavioral switches, which rational individuals also take into account when formulating their Nash-equilibrium strategies. While this modeling approach is general, here we develop it for individuals choosing their "contact rates" within a particular Susceptible-Infected-Recovered-Susceptible-Dead (SIRSD) epidemics model. The latter is based on a frequency-based force of infection and the mortality rate that rapidly increases once the proportion of infected individuals exceeds some prescribed threshold,…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Mathematical and Theoretical Epidemiology and Ecology Models · Evolutionary Game Theory and Cooperation
