Coinfection mechanism is a common interacting mode between multiple diseases in real spreading processes, where the diseases mutually increase their susceptibility, and has aroused widespread studies in network science. We use the bond percolation theory to characterize the coinfection model under two self-awareness control strategies, including immunization strategy and quarantine strategy, and to study the impacts of the synergy effect and control strategies on cooperative epidemics. We find that strengthening the synergy effect can reduce the epidemic threshold and enhance the outbreak size of coinfected networks. On Erdős–Rényi networks, the synergy effect will induce a crossover phenomenon of phase transition, i.e., make the type of phase transition from being continuous to discontinuous. Self-awareness control strategies play a non-negligible role in suppressing cooperative epidemics. In particular, increasing immunization or the quarantine rate can enhance the epidemic threshold and reduce the outbreak size of cooperative epidemics, and lead to a crossover phenomenon of transition from being discontinuous to continuous. The impact of quarantine strategy on cooperative epidemics is more significant than the immunization strategy, which is verified on scale-free networks.
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Research Article|
May 21 2019
Self-awareness control effect of cooperative epidemics on complex networks
Zexun Wang;
Zexun Wang
1
School of Information Science Technology, East China Normal University
, Shanghai 200241, China
2
Web Sciences Center, University of Electronic Science and Technology of China
, Chengdu 611731, China
3
Big Data Research Center, University of Electronic Science and Technology of China
, Chengdu 611731, China
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Ming Tang
;
Ming Tang
a)
1
School of Information Science Technology, East China Normal University
, Shanghai 200241, China
3
Big Data Research Center, University of Electronic Science and Technology of China
, Chengdu 611731, China
4
Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University
, Shanghai 200241, China
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Shimin Cai
;
Shimin Cai
b)
2
Web Sciences Center, University of Electronic Science and Technology of China
, Chengdu 611731, China
3
Big Data Research Center, University of Electronic Science and Technology of China
, Chengdu 611731, China
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Ying Liu;
Ying Liu
3
Big Data Research Center, University of Electronic Science and Technology of China
, Chengdu 611731, China
5
School of Computer Science, Southwest Petroleum University
, Chengdu 610500, China
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Jie Zhou;
Jie Zhou
6
School of Physics and Materials Science, East China Normal University
, Shanghai 200241, China
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Dingding Han
Dingding Han
7
School of Information Science and Technology, Fudan University
, Shanghai 200433, China
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Chaos 29, 053123 (2019)
Article history
Received:
October 03 2018
Accepted:
April 23 2019
Citation
Zexun Wang, Ming Tang, Shimin Cai, Ying Liu, Jie Zhou, Dingding Han; Self-awareness control effect of cooperative epidemics on complex networks. Chaos 1 May 2019; 29 (5): 053123. https://doi.org/10.1063/1.5063960
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