Kinetic SIS opinion-driven models with asymmetric awareness feedback: macroscopic limit and polarization

TL;DR

This paper develops a kinetic multi-agent model linking opinion dynamics with epidemic spreading, revealing how awareness and extremization influence disease and opinion evolution, with a focus on the SIS model.

Contribution

It introduces a novel coupled opinion-epidemic framework with asymmetric awareness feedback and derives a macroscopic limit and reduced differential system.

Findings

Infection events increase cautious opinions and reduce disease spread.

Failed transmissions lead to more extreme opinions and affect epidemic dynamics.

Numerical simulations demonstrate the interplay between awareness and extremization in shaping outcomes.

Abstract

We study a kinetic multi-agent framework coupling opinion dynamics with epidemic spreading, where individual social behaviour both affects and is affected by disease transmission. Each agent is characterised by an epidemiological state and a continuous opinion variable measuring compliance with non-pharmaceutical interventions. The key mechanism of the model is an asymmetric opinion update driven by epidemic encounters: infection events induce more cautious attitudes, while failed transmissions push individuals toward more extreme opinions. We focus on a prototypical SIS setting, for which we derive a macroscopic kinetic description and, in a fast social-interaction regime, a reduced system of differential equations capturing the feedback between epidemic prevalence and opinion evolution. Convergence of the reduced model is rigorously quantified through a modified Wasserstein distance. Numerical simulations highlight how infection-induced awareness and non-infection-driven extremization jointly shape collective epidemic-opinion dynamics.