Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks

Dong Wang, Yi Zhao and Hui Leng
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Dong Wang: School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
Yi Zhao: School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
Hui Leng: School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China

Mathematics, 2020, vol. 8, issue 11, 1-15

Abstract: The co-evolution between information and epidemic in multilayer networks has attracted wide attention. However, previous studies usually assume that two networks with the same individuals are coupled into a multiplex network, ignoring the context that the individuals of each layer in the multilayer network are often different, especially in group structures with rich collective phenomena. In this paper, based on the scenario of group-based multilayer networks, we investigate the coupled UAU-SIS (Unaware-Aware-Unaware-Susceptible-Infected-Susceptible) model via microscopic Markov chain approach (MMCA). Importantly, the evolution of such transmission process with respective to various impact factors, especially for the group features, is captured by simulations. We further obtain the theoretical threshold for the onset of epidemic outbreaks and analyze its characteristics through numerical simulations. It is concluded that the growth of the group size of information (physical) layer effectively suppresses (enhances) epidemic spreading. Moreover, taking the context of epidemic immunization into account, we find that the propagation capacity and robustness of this type of network are greater than the conventional multiplex network.

Keywords: spreading dynamics; group-based networks; MMCA; collective phenomenon; robustness (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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