A Networked Competitive Multi-Virus SIR Model: Analysis and Observability

Ciyuan Zhang, Sebin Gracy, Tamer Basar, Philip E. Paré

Research output: Contribution to journalConference articlepeer-review


This paper proposes a novel discrete-Time multi-virus SIR (susceptible-infected-recovered) model that captures the spread of competing SIR epidemics over a population network. First, we provide a sufficient condition for the infection level of all the viruses over the networked model to converge to zero in exponential time. Second, we propose an observation model which captures the summation of all the viruses' infection levels in each node, which represents the individuals who are infected by different viruses but share similar symptoms. We present a sufficient condition for the model to be locally observable. We propose a Luenberger observer for the system state estimation and show via simulations that the estimation error of the Luenberger observer converges to zero before the viruses die out.

Original languageEnglish (US)
Pages (from-to)13-18
Number of pages6
Issue number13
StatePublished - 2022
Externally publishedYes
Event9th IFAC Conference on Networked Systems, NECSYS 2022 - Zurich, Switzerland
Duration: Jul 5 2022Jul 7 2022


  • Biological network
  • Epidemics dynamics

ASJC Scopus subject areas

  • Control and Systems Engineering


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