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Herd Behaviors in Epidemics: A Dynamics-Coupled Evolutionary Games Approach
Shutian Liu1, Yuhan Zhao1, Quanyan Zhu1
1Department of Electrical and Computer Engineering, Tandon School of Engineering New York University, Brooklyn, NY 11201 USA.
Dynamic Games and Applications
|March 14, 2022
Summary
This study introduces an evolutionary game framework to model how human behavior and infectious disease spread influence each other. The model accurately predicts COVID-19 dynamics, highlighting the interplay between herd behavior and epidemics.
Area of Science:
- Epidemiology
- Game Theory
- Network Science
Background:
- The COVID-19 pandemic highlighted the critical link between human behavior and infectious disease transmission.
- Understanding this interplay is crucial for effective epidemic control strategies.
Purpose of the Study:
- To develop a theoretical framework for studying the coupled evolution of herd behavior and epidemics.
- To analyze how individual social activity choices impact disease spread and vice versa.
Main Methods:
- Coupling an evolutionary game-theoretic model with a mean-field epidemic model on complex networks.
- Analyzing stationary properties of the epidemic and structural properties of the game.
- Developing a structure-preserving approximation for time-dependent dynamics.
Main Results:
- Herd behavior and epidemic dynamics were found to be interdependent, with herd decisions acting as strategic substitutes.
- The proposed framework successfully simulated coupled dynamics.
- The model demonstrated strong resemblance to real-world COVID-19 statistics.
Conclusions:
- The evolutionary game-theoretic framework provides a powerful tool for understanding and predicting the joint evolution of behavior and epidemics.
- The findings underscore the importance of considering behavioral feedback in epidemic modeling.
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