Epidemic threshold in structured scale-free networks

TL;DR

This paper investigates how high clustering and degree correlations in structured scale-free networks influence epidemic spreading, revealing a finite epidemic threshold that contrasts with random networks, thus indicating increased resilience.

Contribution

It introduces a quantitative model linking epidemic thresholds to neighborhood connectivity of hubs in structured scale-free networks.

Findings

Finite epidemic threshold in structured networks

High clustering and correlations increase network resilience

Threshold depends on hub neighborhood connectivity

Abstract

We analyze the spreading of viruses in scale-free networks with high clustering and degree correlations, as found in the Internet graph. For the Suscetible-Infected-Susceptible model of epidemics the prevalence undergoes a phase transition at a finite threshold of the transmission probability. Comparing with the absence of a finite threshold in networks with purely random wiring, our result suggests that high clustering and degree correlations protect scale-free networks against the spreading of viruses. We introduce and verify a quantitative description of the epidemic threshold based on the connectivity of the neighborhoods of the hubs.