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An SIS epidemiology game with two subpopulations
1Department of Mathematics, Pennsylvania State University, University Park, PA, USA. timothy@reluga.org
Journal of Biological Dynamics
|August 14, 2012
Summary
Game theory in epidemiology reveals that how populations mix impacts disease spread. Disassortative mixing can create unstable disease equilibria, while assortative mixing leads to a stable outcome.
Area of Science:
- Epidemiology
- Game Theory
- Mathematical Biology
Background:
- Traditional epidemiological models often assume homogeneous populations.
- Limited research exists on game theory applied to heterogeneous populations in disease dynamics.
Purpose of the Study:
- To analyze rational-expectation equilibria in an epidemiology game with two interacting subpopulations.
- To investigate how individual decisions on prevention affect disease prevalence and transmission patterns.
Main Methods:
- Utilized an SIS (Susceptible-Infected-Susceptible) model for transmission dynamics.
- Analyzed game theory with rational expectations and Nash equilibria.
- Assessed dynamic stability of equilibria under self-interested strategy adjustments.
Main Results:
- Disassortative mixing between subpopulations can result in multiple, unstable Nash equilibria.
- Positively assortative mixing leads to a single, globally stable Nash equilibrium.
- Individual prevention choices significantly influence disease dynamics in interacting populations.
Conclusions:
- Population mixing structure is critical for disease control strategies in game-theoretic epidemiological models.
- Stable disease outcomes are more likely with positively assortative mixing.
- Understanding these dynamics can inform public health interventions.
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