Epidemic incidence in correlated complex networks

TLDR

The study introduces a numerical method to solve epidemic models on the topology of complex networks. The method uses mean‑field rate equations to efficiently simulate epidemic dynamics on large complex networks, enabling analysis of population time profiles. Numerical experiments on assortative networks show no epidemic threshold, and the method can be applied to any mean‑field epidemic model.

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 us to work with very large system sizes, where Monte Carlo simulations are useless due to memory needs. We then study the susceptible-infected-removed 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 us to solve arbitrary epidemiclike models provided that they can be described by mean-field rate equations.