Epidemic Incidence in Correlated Complex Networks

TL;DR

This paper presents a numerical method for analyzing epidemic spread on large complex networks using mean-field rate equations, revealing the absence of epidemic thresholds in assortative networks and enabling study of various epidemic models.

Contribution

Introduces a scalable numerical approach for epidemic modeling on complex networks based on mean-field equations, applicable to large systems and diverse models.

Findings

No epidemic thresholds in assortative networks

Method efficiently handles large network sizes

Time profiles of epidemic populations analyzed

Abstract

We introduce a numerical method to solve epidemic models on the underlying topology of complex networks. The approach exploits the mean-field like rate equations describing the system and allows to work with very large system sizes, where Monte Carlo simulations are useless due to memory needs. We then study the SIR epidemiological model on assortative networks, providing numerical evidence of the absence of epidemic thresholds. Besides, the time profiles of the populations are analyzed. Finally, we stress that the present method would allow to solve arbitrary epidemic-like models provided that they can be described by mean-field rate equations.