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dc.contributor.author
Kröger, Martin
dc.contributor.author
Turkyilmazoglu, Mustafa
dc.contributor.author
Schlickeiser, Reinhard
dc.date.accessioned
2021-07-06T11:47:00Z
dc.date.available
2021-07-04T21:26:47Z
dc.date.available
2021-07-06T11:47:00Z
dc.date.issued
2021-11
dc.identifier.issn
0167-2789
dc.identifier.issn
1872-8022
dc.identifier.other
10.1016/j.physd.2021.132981
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/492902
dc.identifier.doi
10.3929/ethz-b-000492902
dc.description.abstract
An analytic evaluation of the peak time of a disease allows for the installment of effective epidemic precautions. Recently, an explicit analytic, approximate expression (MT) for the peak time of the fraction of infected persons during an outbreak within the susceptible–infectious–recovered/removed (SIR) model had been presented and discussed (Turkyilmazoglu, 2021). There are three existing approximate solutions (SK-I, SK-II, and CG) of the semi-time SIR model in its reduced formulation that allow one to come up with different explicit expressions for the peak time of the infected compartment (Schlickeiser and Kröger, 2021; Carvalho and Gonçalves, 2021). Here we compare the four expressions for any choice of SIR model parameters and find that SK-I, SK-II and CG are more accurate than MT as long as the amount of population to which the SIR model is applied exceeds hundred by far (countries, ss, cities). For small populations with less than hundreds of individuals (families, small towns), however, the approximant MT outperforms the other approximants. To be able to compare the various approaches, we clarify the equivalence between the four-parametric dimensional SIR equations and their two-dimensional dimensionless analogue. Using Covid-19 data from various countries and sources we identify the relevant regime within the parameter space of the SIR model.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Epidemic
en_US
dc.subject
SIR model
en_US
dc.subject
Peak thresholds
en_US
dc.subject
Peak time
en_US
dc.subject
COVID-19
en_US
dc.title
Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2021-06-24
ethz.journal.title
Physica D: Nonlinear Phenomena
ethz.journal.volume
425
en_US
ethz.journal.abbreviated
Physica, D, Nonlinear phenom
ethz.pages.start
132981
en_US
ethz.size
9 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02160 - Dep. Materialwissenschaft / Dep. of Materials::02646 - Institut für Polymere / Institute of Polymers::03359 - Oettinger, Christian / Oettinger, Christian
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02160 - Dep. Materialwissenschaft / Dep. of Materials::02646 - Institut für Polymere / Institute of Polymers::03359 - Oettinger, Christian / Oettinger, Christian
en_US
ethz.date.deposited
2021-07-04T21:26:52Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-07-06T11:47:07Z
ethz.rosetta.lastUpdated
2022-03-29T10:18:07Z
ethz.rosetta.versionExported
true
ethz.COinS
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