Coupling opinion dynamics and epidemiology

TL;DR

This paper models the interplay between opinion dynamics and infectious disease spread, revealing complex behaviors and the importance of social interventions in controlling epidemics.

Contribution

It introduces a coupled mathematical model integrating opinion change and disease transmission, analyzing stability and complex dynamics of the system.

Findings

Complex dynamics including limit cycles and multiple attractors.

Non-monotonic relationship between infectivity and epidemic outcomes.

Behavioral shifts can permanently alter epidemic trajectories.

Abstract

This research investigates the coupled dynamics of behavior and infectious disease using a mathematical model. We integrate a two-state q-voter opinion process with SIS-type infection dynamics, where transmission rates are influenced by the opinion and an infection-induced switching mechanism represents individuals reassessing their behavior upon infection. Analytically, we derive conditions for the stability of endemic and disease-free equilibria. Numerical simulations reveal complex dynamics: above a certain infectivity threshold, the system can exhibit alternative basins of attraction leading to a balanced endemic fixed point or stable limit cycles. Notably, the dominant asymptotic opinion and resulting epidemiological outcomes show non-monotonic relationships with infectivity, highlighting the potential for adaptive behavior to induce complex system dynamics. These findings underscore the critical role of social interventions; shifts in behavioral norms and trust can permanently alter epidemic outcomes, suggesting that such interventions are as crucial as biomedical controls