Novel epidemic models on PSO-based networks.

Journal: Journal of theoretical biology
Published Date:

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.

Authors

  • Dongmei Fan
    School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; School of Science, Anhui Agricultural University, Hefei 230036, China.
  • Guo-Ping Jiang
    School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
  • Yu-Rong Song
    School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China. Electronic address: songyr@njupt.edu.cn.
  • Yin-Wei Li
    School of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
  • Guanrong Chen
    Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China.