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Effects of active links on epidemic transmission over social networks

  • Guanghu Zhu
  • , Guanrong Chen
  • , Xinchu Fu*
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

A new epidemic model with two infection periods is developed to account for the human behavior in social network, where newly infected individuals gradually restrict most of future contacts or are quarantined, causing infectivity change from a degree-dependent form to a constant. The corresponding dynamics are formulated by a set of ordinary differential equations (ODEs) via mean-field approximation. The effects of diverse infectivity on the epidemic dynamics ​are examined, with a behavioral interpretation of the basic reproduction number. Results show that such simple adaptive reactions largely determine the impact of network structure on epidemics. Particularly, a theorem proposed by Lajmanovich and Yorke in 1976 is generalized, so that it can be applied for the analysis of the epidemic models with multi-compartments especially network-coupled ODE systems.
Original languageEnglish
Pages (from-to)614-621
JournalPhysica A: Statistical Mechanics and its Applications
Volume468
Online published25 Oct 2016
DOIs
Publication statusPublished - 15 Feb 2017

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

  • Adaptive behavior
  • Basic reproduction number
  • Contact network
  • Infectivity

RGC Funding Information

  • RGC-funded

Policy Impact

  • Cited in Policy Documents

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