Game-Theoretic Protection Adoption Against Networked SIS Epidemics

TL;DR

This paper models how individuals in a network strategically adopt protection against SIS epidemics, analyzing the equilibrium states and effects of various parameters on epidemic prevalence.

Contribution

It introduces a game-theoretic framework for protection strategies in networked SIS epidemics and characterizes the unique endemic equilibrium.

Findings

Existence and uniqueness of endemic equilibrium established.

Protection effectiveness and network heterogeneity significantly influence epidemic prevalence.

Optimal strategies depend on individual degree and epidemic state.

Abstract

In this paper, we investigate game-theoretic strategies for containing spreading processes on large-scale networks. Specifically, we consider the class of networked susceptible-infected-susceptible (SIS) epidemics where a large population of agents strategically choose whether to adopt partially effective protection. We define the utilities of the agents which depends on the degree of the agent, its individual infection status and action, as well as the the overall prevalence of the epidemic and strategy profile of the entire population. We further present the coupled dynamics of epidemic evolution as well as strategy update which is assumed to follow the replicator dynamics. By relying on timescale separation arguments, we first derive the optimal strategy of protection adoption by the agents for a given epidemic state, and then present the reduced epidemic dynamics. The existence and uniqueness of endemic equilibrium is rigorously characterized and forms the main result of this paper. Finally, we present extensive numerical results to highlight the impacts of heterogeneous node degrees, infection rates, cost of protection adoption, and effectiveness of protection on the epidemic prevalence at the equilibrium.