Traffic-driven SIR epidemic model on networks

TL;DR

This paper introduces a traffic-driven SIR epidemic model on networks where infection spreads via packets, showing how routing strategies and network properties influence epidemic dynamics and spread.

Contribution

It presents a novel infection transmission model based on packet flow and analyzes how routing and network structure affect epidemic spread.

Findings

Balanced load distribution increases epidemic spread.

Higher average degree or degree homogeneity facilitates spreading.

High packet generation rate initially promotes, then inhibits epidemic due to congestion.

Abstract

We propose a novel SIR epidemic model which is driven by the transmission of infection packets in networks. Specifically, infected nodes generate and deliver infection packets causing the spread of the epidemic, while recovered nodes block the delivery of infection packets, and this inhibits the epidemic spreading. The efficient routing protocol governed by a control parameter $\alpha$ is used in the packet transmission. We obtain the maximum instantaneous population of infected nodes, the maximum population of ever infected nodes, as well as the corresponding optimal $\alpha$ through simulation. We find that generally more balanced load distribution leads to more intense and wide spread of an epidemic in networks. Increasing either average node degree or homogeneity of degree distribution will facilitate epidemic spreading. When packet generation rate $\rho$ is small, increasing $\rho$ favors epidemic spreading. However, when $\rho$ is large enough, traffic congestion appears which inhibits epidemic spreading.