How opinions shape epidemics: a graphon-based kinetic approach

TL;DR

This paper introduces a graphon-based kinetic framework to model the complex interplay between opinions, social contacts, and disease transmission, providing insights into epidemic control strategies.

Contribution

It develops a novel multiscale mathematical model combining opinion dynamics, physical contacts, and epidemic spread on large-scale social networks using graphons.

Findings

The model captures heterogeneous social structures and contact patterns.

Numerical experiments show how shaping opinions can influence epidemic outcomes.

The framework enables analysis of coupled opinion-epidemic evolution.

Abstract

Understanding the mutual influence between social behavior and physical health is crucial for designing effective epidemic mitigation strategies. Individual interactions drive the evolution of opinions, which in turn shape how infectious diseases are perceived and consequently how they spread within a population, for instance through the adoption or rejection of preventive measures. At the same time, the distribution and dynamics of physical contacts play a fundamental role in determining transmission patterns. To this end, we develop a mathematical framework to analyze the coupled dynamics of opinion formation, disease transmission, and physical contacts by employing graphon-based networks, which capture heterogeneous and large-scale connectivity patterns typical of realistic social structures. The epidemic compartmental model further incorporates a kinetic description of microscopic level physical contacts, allowing for a consistent multiscale representation of interaction patterns. Starting from a microscopic description governed by interpersonal compromise and intrinsic self-thinking processes, we derive a kinetic compartmental epidemic model on graphons via a mean-field limit. This formulation allows us to investigate the joint evolution of the disease state and the opinion distribution, with a particular focus on the role of social networks and physical contacts. Numerical experiments demonstrate that the graphon-kinetic approach provides a comprehensive representation of the coupled opinion-epidemic dynamics, revealing new possibilities for controlling disease spread by shaping population opinion patterns.