Stability analysis and control of virus spread over time-varying networks

Philip E. Pare, Carolyn L. Beck, Angelia Nedich

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

8 Citations (Scopus)

Abstract

Virus models are used commonly for modeling and analysis of biological networks, computer networks, and human contact networks. The dynamic modeling of such systems in prior work has mainly been focused on networks with static graph structures, which we posit are unrealistic and/or oversimplified for the purpose of understanding and analyzing disease propagation of viruses. In this paper, we consider network models with dynamic graph structures, and investigate the propagation and inhibition of diseases in these systems. A stability analysis of the model we consider is performed, examining the disease free equilibrium conditions. Quarantine is proposed as one control technique. Various network simulations are presented and a number of conjectures are given based on these simulations.

Original languageEnglish (US)
Title of host publication2015 54th IEEE Conference on Decision and Control, CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3554-3559
Number of pages6
Volume2016-February
ISBN (Electronic)9781479978861
DOIs
StatePublished - Feb 8 2016
Externally publishedYes
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
CountryJapan
CityOsaka
Period12/15/1512/18/15

Fingerprint

Time varying networks
Viruses
Virus
Stability Analysis
Time-varying
Quarantine
Propagation
Dynamic Graphs
Network Simulation
Biological Networks
Computer Networks
Dynamic Modeling
Computer networks
Network Model
Contact
Graph in graph theory
Modeling
Model
Simulation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

Pare, P. E., Beck, C. L., & Nedich, A. (2016). Stability analysis and control of virus spread over time-varying networks. In 2015 54th IEEE Conference on Decision and Control, CDC 2015 (Vol. 2016-February, pp. 3554-3559). [7402769] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2015.7402769

Stability analysis and control of virus spread over time-varying networks. / Pare, Philip E.; Beck, Carolyn L.; Nedich, Angelia.

2015 54th IEEE Conference on Decision and Control, CDC 2015. Vol. 2016-February Institute of Electrical and Electronics Engineers Inc., 2016. p. 3554-3559 7402769.

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

Pare, PE, Beck, CL & Nedich, A 2016, Stability analysis and control of virus spread over time-varying networks. in 2015 54th IEEE Conference on Decision and Control, CDC 2015. vol. 2016-February, 7402769, Institute of Electrical and Electronics Engineers Inc., pp. 3554-3559, 54th IEEE Conference on Decision and Control, CDC 2015, Osaka, Japan, 12/15/15. https://doi.org/10.1109/CDC.2015.7402769
Pare PE, Beck CL, Nedich A. Stability analysis and control of virus spread over time-varying networks. In 2015 54th IEEE Conference on Decision and Control, CDC 2015. Vol. 2016-February. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3554-3559. 7402769 https://doi.org/10.1109/CDC.2015.7402769
Pare, Philip E. ; Beck, Carolyn L. ; Nedich, Angelia. / Stability analysis and control of virus spread over time-varying networks. 2015 54th IEEE Conference on Decision and Control, CDC 2015. Vol. 2016-February Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3554-3559
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