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Novel epidemic models on PSO-based networks

Dongmei Fan, Guo-Ping Jiang, Yu-Rong Song*, Yin-Wei Li, Guanrong Chen

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This paper proposes two spatio-temporal epidemic network models based on popularity and similarity optimization (PSO), called r-SI and r-SIS, respectively, in which new connections take both popularity and similarity into account. In the spatial dimension, the epidemic process is described by the diffusion equation; in the time dimension, the growth of an epidemic is described by the logistic map. Both models are represented by partial differential equations, and can be easily solved. Simulations are performed on both artificial and real networks, demonstrating the effectiveness of the two models.
Original languageEnglish
Pages (from-to)36-43
JournalJournal of Theoretical Biology
Volume477
Online published10 Jun 2019
DOIs
Publication statusPublished - 21 Sept 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • Epidemic dynamics
  • Hyperbolic space
  • Popularity
  • Similarity

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