Spreading of Epidemics on Scale-Free Networks with Traffic Flow

Ya-Qi Wang, Guoping Jiang
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Abstract

In this paper, based on the mean-field theory, we propose a new susceptible-infected-removed (SIR) model to study epidemic spreading on scale-free networks with traffic flow. Theoretical analysis shows that as the network traffic flow increases, the epidemic prevalence is obviously enhanced, and the epidemic threshold is reduced. We also find that the epidemic threshold is related to the ratio between the first and second moments of the network’s algorithm betweenness distribution. Moreover, the heterogeneity levels of the networks weaken the epidemic spreading. We confirm all results by sufficient numerical simulations.
具有交通流的无标度网络中流行病的传播
本文基于平均场理论,提出了一种新的敏感-感染-去除(SIR)模型来研究具有交通流的无标度网络上的流行病传播。理论分析表明,随着网络流量的增加,流行程度明显增强,流行阈值降低。我们还发现,流行阈值与网络算法间度分布的第一阶矩与第二阶矩之比有关。此外,网络的异质性程度削弱了流行病的传播。我们通过充分的数值模拟证实了所有结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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