Interaction between cluster synchronization and epidemic spread in community networks

TL;DR

This paper develops a mathematical model to analyze how cluster synchronization of human behaviors within community networks influences epidemic spread, providing theoretical insights and numerical validation.

Contribution

It introduces the first model addressing the interaction between cluster synchronization and epidemic transmission in community networks, integrating behavioral evolution and epidemic dynamics.

Findings

Epidemic threshold derived using Gersgorin Lemma and dynamical systems theory.

Stability conditions for cluster synchronization and epidemic spread established.

Numerical simulations confirm theoretical results and illustrate behavior interactions.

Abstract

In real world, there is a significant relation between human behaviors and epidemic spread. Especially, the reactions among individuals in different communities to epidemics may be different, which lead to cluster synchronization of human behaviors. So, a mathematical model that embeds community structures, behavioral evolution and epidemic transmission is constructed to study the interaction between cluster synchronization and epidemic spread. The epidemic threshold of the model is obtained by using Gersgorin Lemma and dynamical system theory. By applying the Lyapunov stability method, the stability analysis of cluster synchronization and spreading dynamics are presented. Then, some numerical simulations are performed to illustrate and complement our theoretical results. As far as we know, this work is the first one to address the interplay between cluster synchronization and epidemic transmission in community networks, so it may deepen the understanding of the impact of cluster behaviors on infectious disease dynamics.