Epidemic Spreading in Weighted Networks: An Edge-Based Mean-Field Solution

TL;DR

This paper develops an edge-based mean-field approach to accurately model epidemic spreading on weighted networks, revealing how weight distribution homogeneity influences epidemic prevalence.

Contribution

It introduces a novel edge-based mean-field solution that captures the effects of weight distribution on epidemic dynamics, surpassing traditional methods.

Findings

Homogeneous weight distributions lead to higher epidemic prevalence.

Traditional mean-field approximations fail to capture the impact of weight distribution.

The proposed method accurately reproduces simulation results for various weight distributions.

Abstract

Weight distribution largely impacts the epidemic spreading taking place on top of networks. This paper studies a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could find its applications in characterizing the non-equilibrium steady states of dynamical processes on weighted networks.