Cooperate epidemic spreading on multiplex networks with heterogeneous population

Tianqiao Zhang, Yang Zhang, Jinming Ma, Junliang Chen and Xuzhen Zhu
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Tianqiao Zhang: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China†School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
Yang Zhang: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
Jinming Ma: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
Junliang Chen: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
Xuzhen Zhu: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

International Journal of Modern Physics C (IJMPC), 2020, vol. 31, issue 09, 1-10

Abstract: Cooperate epidemic spreading dynamics has attracted much attention from the field of network science. In this paper, we study the cooperate epidemic spreading dynamics on multiplex networks with heterogeneous populations, which induces the heterogeneous coinfection susceptibility. We propose a spreading model to describe the evolution mechanisms. To predict the final state of the epidemic outbreak size, a generalized bond percolation theory is suggested. Through numerical simulations and theoretical analyses, we find that the system exhibits a discontinuous phase transition for large average and small variance of the distribution of coinfection susceptibility on ER–ER multiplex networks, while the phase transition is continuous on SF–SF networks. In addition, the final outbreak size increases with the average coinfection susceptibility and decreases with the variance of the coinfection susceptibility. Our suggested bond percolation theory can well predict the numerical simulations.

Keywords: Cooperate epidemic spreading; multiplex networks; phase transition (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0129183120501326

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