Network-Based Epidemic Control Through Optimal Travel and Quarantine Management.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	Network-Based Epidemic Control Through Optimal Travel and Quarantine Management.
Συγγραφείς:	Talaei M; Department of Electrical and Computer Engineering, and the Division of Systems Engineering, Boston University, Boston, MA, USA., Rikos AI; Department of Electrical and Computer Engineering, and the Division of Systems Engineering, Boston University, Boston, MA, USA., Olshevsky A; Department of Electrical and Computer Engineering, and the Division of Systems Engineering, Boston University, Boston, MA, USA., White LF; School of Public Health, Boston University, Boston, MA, USA., Paschalidis IC; Department of Electrical and Computer Engineering, and the Division of Systems Engineering, Boston University, Boston, MA, USA.; Department of Biomedical Engineering and the Faculty for Computing & Data Sciences, Boston University, Boston, MA, USA.
Πηγή:	IEEE transactions on control of network systems [IEEE Trans Control Netw Syst] 2025 Dec; Vol. 12 (4), pp. 2726-2738. Date of Electronic Publication: 2025 Jul 18.
Τύπος έκδοσης:	Journal Article
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101721948 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2325-5870 (Electronic) Linking ISSN: 23255870 NLM ISO Abbreviation: IEEE Trans Control Netw Syst Subsets: PubMed not MEDLINE
Imprint Name(s):	Original Publication: Piscataway, New Jersey : Institute of Electrical and Electronics Engineers, 2014-
Περίληψη:	Motivated by the swift global transmission of infectious diseases, we present a comprehensive framework for network-based epidemic control. Our aim is to curb epidemics using two different approaches. In the first approach, we introduce an optimization strategy that optimally reduces travel rates. We analyze the convergence of this strategy and show that it hinges on the network structure to minimize infection spread. In the second approach, we expand the classic SIR model by incorporating and optimizing quarantined states to strategically contain the epidemic. We show that this problem reduces to the problem of matrix balancing. We establish a link between optimization constraints and the epidemic's reproduction number, highlighting the relationship between network structure and disease dynamics. We demonstrate that applying augmented primal-dual gradient dynamics to the optimal quarantine problem ensures exponential convergence to a stationary point. We conclude by validating our approaches using simulation studies that leverage public data from counties in the state of Massachusetts.
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Grant Information:	UL1 TR001430 United States TR NCATS NIH HHS
Contributed Indexing:	Keywords: Epidemics; compartmental models; networked control systems; optimization; stability of nonlinear systems
Entry Date(s):	Date Created: 20260126 Latest Revision: 20260920
Update Code:	20260920
PubMed Central ID:	PMC12830048
DOI:	10.1109/tcns.2025.3590383
PMID:	41585447
Βάση Δεδομένων:	MEDLINE

Περιγραφή
ISSN:	2325-5870
DOI:	10.1109/tcns.2025.3590383