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Suppressing the endemic equilibrium in SIS epidemics: A state dependent approach
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-2136-3957
Tokyo Inst Technol, Dept Comp Sci, Yokohama, Kanagawa, Japan..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9940-5929
2021 (English)In: IFAC PAPERSONLINE, Elsevier BV , 2021, Vol. 54, no 15, p. 163-168Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers the susceptible-infected-susceptible (SIS) epidemic model with an underlying network structure and focuses on the effect of social distancing to regulate the epidemic level. We demonstrate that if each subpopulation is informed of its infection rate and reduces interactions accordingly, the fraction of the subpopulation infected stays below half for all time instants. To this end, we first modify the basic SIS model by introducing a state dependent parameter representing the frequency of interactions between subpopulations. Thereafter, we show that for this modified SIS model, the spectral radius of a suitably-defined matrix being not greater than one causes all the agents, regardless of their initial sickness levels, to converge to the healthy state; assuming non-trivial disease spread, the spectral radius being greater than one leads to the existence of a unique endemic equilibrium, which is also asymptotically stable. Finally, by leveraging the aforementioned results, we show that the fraction of (sub)populations infected never exceeds half. Copyright

Place, publisher, year, edition, pages
Elsevier BV , 2021. Vol. 54, no 15, p. 163-168
Keywords [en]
Epidemic processes, Infection reduction, Characterization of endemic equilibrium, Suppressing endemic equilibrium
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-305499DOI: 10.1016/j.ifacol.2021.10.249ISI: 000714393600028Scopus ID: 2-s2.0-85120713218OAI: oai:DiVA.org:kth-305499DiVA, id: diva2:1615804
Conference
11th IFAC Symposium on Biological and Medical Systems (BMS), SEP 19-22, 2021, Ghent, BELGIUM
Note

QC 20211201

Available from: 2021-12-01 Created: 2021-12-01 Last updated: 2022-06-25Bibliographically approved

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Wang, YuanGracy, SebinJohansson, Karl H.

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