Epidemic spreading on complex networks with general degree and weight distributions

被引：129

作者：

Wang, Wei ^{[1
]}

Tang, Ming ^{[1
,2
]}

Zhang, Hai-Feng ^{[3
]}

Gao, Hui ^{[1
]}

Do, Younghae ^{[4
]}

Liu, Zong-Hua ^{[5
]}

机构：

[1] Univ Elect Sci & Technol China, Web Sci Ctr, Chengdu 610054, Peoples R China

[2] Kyungpook Natl Univ, Ctr Atmospher Remote Sensing CARE, Taegu 702701, South Korea

[3] Anhui Univ, Sch Math Sci, Hefei 230039, Peoples R China

[4] Kyungpook Natl Univ, Dept Math, Taegu 702701, South Korea

[5] E China Normal Univ, Dept Phys, Shanghai 200062, Peoples R China

来源：

PHYSICAL REVIEW E | 2014年 / 90卷 / 04期

基金：

新加坡国家研究基金会; 中国国家自然科学基金;

关键词：

SIR DYNAMICS;

D O I：

10.1103/PhysRevE.90.042803

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

The spread of disease on complex networks has attracted wide attention in the physics community. Recent works have demonstrated that heterogeneous degree and weight distributions have a significant influence on the epidemic dynamics. In this study, a novel edge-weight-based compartmental approach is developed to estimate the epidemic threshold and epidemic size (final infected density) on networks with general degree and weight distributions, and a remarkable agreement with numerics is obtained. Even in complex networks with the strong heterogeneous degree and weight distributions, this approach is used. We then propose an edge-weight-based removal strategy with different biases and find that such a strategy can effectively control the spread of epidemic when the highly weighted edges are preferentially removed, especially when the weight distribution of a network is extremely heterogenous. The theoretical results from the suggested method can accurately predict the above removal effectiveness.

引用

页数：8

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