A Bi-Virus Competing Spreading Model with Generic Infection Rates

Lu-Xing Yang, Xiaofan Yang, Yuan Yan Tang

Research output: Contribution to journalArticleScientificpeer-review

68 Citations (Scopus)


Due to widespread applications, the multi-virus competing spreading dynamics has recently aroused considerable interests. To our knowledge, all previous competing spreading models assume infection rates that are each linear in the virus occupancy probabilities of the individuals in a population. As linear infection rates are overestimation of real infection rates, in some situations these models cannot accurately predict the spreading process of multiple competing viruses. This work takes the first step toward enhancing the accuracy of multi-virus competing spreading models. A continuous-time bilayer-network-based bi-virus competing spreading model with generic infection rates is proposed. Criteria for the extinction of both viruses and for the survival of only one virus are presented, respectively. Numerical examples show that (1) if the generic bi-virus spreading model with linear infection rates predicts that the fraction of nodes infected with some virus would approach zero, the prediction of the fraction is accurate, and (2) if the scenario-relevant generic infection rates could be estimated accurately, the resulting model would be able to accurately forecast the evolutionary process of a pair of competing viruses.

Original languageEnglish
Pages (from-to)2-13
Number of pages12
JournalIEEE Transactions on Network Science and Engineering
Issue number1
Publication statusPublished - 2018


  • Analytical models
  • Competing viruses
  • Computational modeling
  • equilibrium
  • generic infection rate
  • global attractivity
  • global stability
  • linear infection rate
  • multilayer network
  • Predictive models
  • Silicon
  • Sociology
  • Statistics
  • virus spreading model
  • Viruses (medical)


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