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Epidemic Spreading and Equilibrium Social Distancing in Heterogeneous Networks.
1Georgia State University, Atlanta, GA 30303 USA.
Dynamic Games and Applications
|January 10, 2022
Summary
This study introduces a network-based SIR epidemic model to analyze disease spread and social distancing strategies. Voluntary social distancing is found to be socially sub-optimal in random regular graphs.
Area of Science:
- Epidemiology
- Network Science
- Game Theory
Background:
- Epidemic modeling is crucial for understanding disease spread in populations.
- Network structures significantly influence disease transmission dynamics.
- Social distancing strategies are key interventions in epidemic control.
Purpose of the Study:
- To analyze a multi-type SIR epidemic process on a heterogeneous population network.
- To establish the epidemic reproduction number based on social distancing strategies.
- To investigate the equilibrium of a social distancing game and its social optimality.
Main Methods:
- Utilizing a random graph model for social contacts with specified vertex degrees.
- Developing limit theorems for the fraction of infected individuals.
- Analyzing the equilibrium conditions for individual social distancing choices based on anticipated infection rates.
Main Results:
- Established the epidemic reproduction number () to assess network vulnerability and guide vaccination policies.
- Identified conditions for the existence and uniqueness of a social distancing game equilibrium.
- Demonstrated that voluntary social distancing is socially sub-optimal in random regular graphs.
Conclusions:
- The study provides a framework for understanding epidemic dynamics in networked populations.
- The findings highlight the limitations of voluntary social distancing as a socially optimal strategy.
- Results can inform public health policies and network-based intervention strategies.
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