Suppression of epidemic spreading in time-varying multiplex networks

Hui Yang, Changgui Gu, Ming Tang, Shi Min Cai, Ying Cheng Lai

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Suppressing and preventing epidemic spreading is of critical importance to the well being of the human society. To uncover phenomena that can guide control and management of epidemics is thus of significant value. An understanding of epidemic spreading dynamics in the real world requires the following two ingredients. Firstly, a multiplex network description is necessary, because information diffusion in the virtual communication layer of the individuals can affect the disease spreading dynamics in the physical contact layer, and vice versa. The interaction between the dynamical processes in the two layers is typically asymmetric. Secondly, both network layers are in general time varying. In spite of the large body of literature on spreading dynamics in complex networks, the effect of the asymmetrical interaction between information diffusion and epidemic spreading in activity-driven, time-varying multiplex networks have not been understood. We address this problem by developing a general theory based on the approach of microscopic Markov chain, which enables us to predict the epidemic threshold and the final infection density in the physical layer, on which the information diffusion process in the virtual layer can have a significant effect. The focus of our study is on uncovering and understanding mechanisms to inhibit physical disease spreading. We find that stronger heterogeneity in the individual activities and a smaller contact capacity in the communication layer can promote the inhibitory effect. A remarkable phenomenon is that an enhanced positive correlation between the activities in the two layers can greatly suppress the spreading dynamics, suggesting a practical and effective approach to controlling epidemics in the real world.

Original languageEnglish (US)
Pages (from-to)806-818
Number of pages13
JournalApplied Mathematical Modelling
Volume75
DOIs
StatePublished - Nov 1 2019
Externally publishedYes

Fingerprint

Epidemic Spreading
Time-varying
Information Diffusion
Network layers
Communication
Complex networks
Markov processes
Contact
Interaction
Complex Networks
Diffusion Process
Infection
Markov chain
Predict
Necessary

Keywords

  • Epidemic spreading
  • Microscopic Markov chain
  • Multiplex network
  • Time-varying

ASJC Scopus subject areas

  • Modeling and Simulation
  • Applied Mathematics

Cite this

Suppression of epidemic spreading in time-varying multiplex networks. / Yang, Hui; Gu, Changgui; Tang, Ming; Cai, Shi Min; Lai, Ying Cheng.

In: Applied Mathematical Modelling, Vol. 75, 01.11.2019, p. 806-818.

Research output: Contribution to journalArticle

Yang, Hui ; Gu, Changgui ; Tang, Ming ; Cai, Shi Min ; Lai, Ying Cheng. / Suppression of epidemic spreading in time-varying multiplex networks. In: Applied Mathematical Modelling. 2019 ; Vol. 75. pp. 806-818.
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