Integrating evolutionary game theory with SEIRS models: A spatial epidemic simulator for strategy-based interventions

This study investigates how adaptive individual behavior influences epidemic dynamics in spatially structured populations. Specifically, it examines how payoff-driven strategy evolution interacts with spatial SEIRS dynamics to shape epidemic outcomes.

We construct a simulation framework that integrates a spatial SEIRS epidemic model with evolutionary game dynamics based on a Hawk-Dove formulation of behavioral strategies, including vaccination and freeriding. Strategies evolve through payoff-driven adaptation driven by local interactions, while disease transmission follows spatially localized SEIRS dynamics on a two-dimensional lattice. All core scenarios were repeated N=15 times with independent random seeds; results are reported as mean ± standard deviation (SD) with 95% confidence intervals.

Behavioral adaptation and spatial structure strongly affect epidemic outcomes. Under high infection penalty (λ=3), epidemics in populations without freeriders were rapidly suppressed (7.0±8.2 cumulative deaths; 95% CI: 2.9-11.1). Introducing 1000 permanent freeriders (62.5% of the population) raised mortality to 187.1±75.0 deaths (95% CI: 149.2-225.1) and extended epidemic duration to 376.4±58.1 generations. Under low infection penalty (λ=1), mortality reached 187.3±25.0 deaths even without freeriders, confirming that perceived infection severity is a key driver of vaccination uptake. Two-dimensional sensitivity sweeps identify a critical freerider cluster size of approximately 300-500 agents (corresponding to 15.6-31.3% of the 1600-agent population used in the main analysis) and a sharp vaccination-cost threshold near C_vac≈0.2-0.5, beyond which epidemic duration approaches the full simulation window regardless of transmission rate.

The framework reveals key feedbacks between individual decision-making and epidemic spread, highlighting the limitations of voluntary vaccination in the presence of permanent non-compliant agents and low perceived infection risk.