Impact of inter-layer hopping on epidemic spreading in a multilayer network

Dayu Wu, Ming Tang, Zonghua Liu, Ying Cheng Lai

Research output: Contribution to journalArticle

Abstract

Hopping of individuals among distinct layers can induce inter-layer coupling and consequently affect the spreading process in each layer of real world multilayer networks. We articulate a two-layer network model where a fraction of nodes are inter-layer travelers that can hop between layers. We develop a theoretical framework based on the quenched mean-field approximation to accurately predict the epidemic thresholds and final states in both layers. Extensive numerical simulations on synthetic and empirical networks demonstrate that, in the general setting where the structures of the two network layers are asymmetric, intense hopping can lead to simultaneous epidemic outbreak in both layers. In general, the impacts of hopping on the spreading dynamics in the two layers can be quite distinct. As the inter-layer coupling strength is increased, the epidemic threshold of the denser layer increases monotonically, while for the sparser layer, a surprising non-monotonic behavior of the threshold with a minimize value arises. Another finding is that, as a result of hopping, recurrent outbreaks can occur in the sparser layer, providing a plausible explanation for the phenomenon of multiple outbreaks observed from real health data.

Original languageEnglish (US)
Article number105403
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume90
DOIs
StatePublished - Nov 2020

Keywords

  • Epidemic spreading
  • Inter-layer hopping
  • Multiplex network
  • Quenched mean-field

ASJC Scopus subject areas

  • Numerical Analysis
  • Modeling and Simulation
  • Applied Mathematics

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