Modeling and analysis of epidemic spreading on community networks with heterogeneity

doi:10.1016/j.jpdc.2018.04.009

Journal of Parallel and Distributed Computing

Volume 119, September 2018, Pages 136-145

https://doi.org/10.1016/j.jpdc.2018.04.009 Get rights and content

Highlights

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A modified community network model with heterogeneity among communities is proposed.
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A mathematical epidemic model for each community is presented based on this network.
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Study the effect of the location of initial infection node on epidemic spreading.
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Study the impact of the heterogeneity among communities on epidemic spreading.

Abstract

A large number of real world networks exhibit community structure, and different communities may often possess heterogeneity. In this paper, considering the heterogeneity among communities, we construct a new community network model in which the communities show significant differences in average degree. Based on this heterogeneous community network, we propose a novel mathematical epidemic model for each community and study the epidemic dynamics in this network model. We find that the location of the initial infection node only affects the spreading velocity and barely influences the epidemic prevalence. And the epidemic threshold of entire network decreases with the increase of heterogeneity among communities. Moreover, the epidemic prevalence increases with the increase of heterogeneity around the epidemic threshold, while the converse situation holds when the infection rate is much greater than the epidemic threshold.

Keywords

Community structure

Heterogeneity

Epidemic dynamics

Mean-field theory

Cited by (0)

Chanchan Li was born in Shanxi, China, in 1989. She is a Ph.D. candidate in school of computer at Nanjing University of Posts and Telecommunications. Her current research interests include information security and complex dynamical networks.

Guo-ping Jiang, Professor and Ph.D., doctoral supervisor of Nanjing University of Posts and Telecommunications. His research interests include chaos synchronization and control, chaos-based communication, and complex dynamical networks.

Yurong Song, Professor and Ph.D., doctoral supervisor of Nanjing University of Posts and Telecommunications. Her recent research interests include information dissemination and its control strategies in complex networks; modeling, simulation and intelligent optimization of adaptive networks.

Lingling Xia was born in Jiangsu, China, in 1988. She gets a Ph.D. in information security this year at Nanjing University of Posts and Telecommunications. Her research interests include information security and information propagation dynamics in complex networks.

Yinwei Li was born in Shandong, China, in 1981. He is a Ph.D. candidate in school of computer at Nanjing University of Posts and Telecommunications. His current research interests include information security and complex dynamical networks.

Bo Song was born in Shandong, China, in 1987. He is now a Ph.D. candidate both in faculty of engineering and information technology at University of Technology Sydney and in school of computer at Nanjing University of Posts and Telecommunications. His research interests include information security and modeling, simulation and intelligent optimization of adaptive networks.

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