On a continuous-time multi-group bi-virus model with human awareness

Ji Liu, Philip E. Paré, Angelia Nedich, Carolyn L. Beck, Tamer Başar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper studies the effect of human awareness on a distributed continuous-time bi-virus model in which two competing viruses diffuse over a network comprised of multiple groups of individuals. When contacting infected individuals in their own and neighboring groups, individuals may either be infected by one of the two viruses with a virus-dependent infection rate or become alert. Alert individuals may be infected by either virus but with a smaller virus-dependent infection rate, and the alert state also diffuses over the network. Limiting behaviors of the model are studied by analyzing the equilibria of the system and their stability. Both equilibria and their stability are compared with those of the model without human awareness.

Original languageEnglish (US)
Title of host publication2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4124-4129
Number of pages6
Volume2018-January
ISBN (Electronic)9781509028733
DOIs
StatePublished - Jan 18 2018
Event56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia
Duration: Dec 12 2017Dec 15 2017

Other

Other56th IEEE Annual Conference on Decision and Control, CDC 2017
CountryAustralia
CityMelbourne
Period12/12/1712/15/17

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ASJC Scopus subject areas

  • Decision Sciences (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Control and Optimization

Cite this

Liu, J., Paré, P. E., Nedich, A., Beck, C. L., & Başar, T. (2018). On a continuous-time multi-group bi-virus model with human awareness. In 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017 (Vol. 2018-January, pp. 4124-4129). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2017.8264265