Multiple Vectors Propagation of Epidemics in Complex Networks

TL;DR

This paper analyzes how epidemics spread in complex networks with two vectors, providing theoretical tools to calculate thresholds and outbreak sizes, revealing that correlations influence epidemic dynamics.

Contribution

It introduces a detailed theoretical framework for epidemic spreading in two-vectors propagation networks, highlighting the effects of degree correlations.

Findings

Epidemics can spread even if individual networks are below their thresholds.

Positive degree-degree correlation lowers the epidemic threshold.

Neighbor similarity has no effect on epidemic threshold or size.

Abstract

This letter investigates the epidemic spreading in two-vectors propagation network (TPN). We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemics can spread across the TPN even if two sub-single-vector propagation networks (SPNs) of TPN are well below their respective epidemic thresholds. Strong positive degree-degree correlation of nodes in TPN could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity between the neighbors from different SPNs of nodes has no effect on the epidemic threshold and outbreak size.