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

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.

7 pages, 5 figures

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• Unification of theoretical approaches for epidemic spreading on complex networks
• Coevolution spreading in complex networks
• Epidemic spreading on complex networks with general degree and weight distributions
• Suppressing disease spreading by using information diffusion on multiplex networks
• Epidemic Spreading on Weighted Complex Networks
• Random walks in weighted networks with a perfect trap: An application of Laplacian spectra
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• Roles of Ties in Spreading
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• Predicting epidemics on weighted networks
• A Jump Stochastic Differential Equation Approach for Influence Prediction on Information Propagation Networks