A Novel Parametric Model for the Prediction and Analysis of the COVID-19 Casualties

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dc.authoridPolat, Adem/0000-0002-5662-4141
dc.authoridBALIKCI, KEMAL/0000-0001-6234-5627
dc.authoridTutsoy, Onder/0000-0001-6385-3025
dc.contributor.authorTutsoy, Önder
dc.contributor.authorColak, Sule
dc.contributor.authorPolat, Adem
dc.contributor.authorBalikci, Kemal
dc.date.accessioned2025-01-06T17:37:15Z
dc.date.available2025-01-06T17:37:15Z
dc.date.issued2020
dc.description.abstractCoronavirus disease (COVID-19) outbreak has affected billions of people, where millions of them have been infected and thousands of them have lost their lives. In addition, to constraint the spread of the virus, economies have been shut down, curfews and restrictions have interrupted the social lives. Currently, the key question in minds is the future impacts of the virus on the people. It is a fact that the parametric modelling and analyses of the pandemic viruses are able to provide crucial information about the character and also future behaviour of the viruses. This paper initially reviews and analyses the Susceptible-Infected-Recovered (SIR) model, which is extensively considered for the estimation of the COVID-19 casualties. Then, this paper introduces a novel comprehensive higher-order, multi-dimensional, strongly coupled, and parametric Suspicious-Infected-Death (SpID) model. The mathematical analysis results performed by using the casualties in Turkey show that the COVID-19 dynamics are inside the slightly oscillatory, stable (bounded) region, although some of the dynamics are close to the instability region (unbounded). However, analysis with the data just after lifting the restrictions reveals that the dynamics of the COVID-19 are moderately unstable, which would blow up if no actions are taken. The developed model estimates that the number of the infected and death individuals will converge zero around 300 days whereas the number of the suspicious individuals will require about a thousand days to be minimized under the current conditions. Even though the developed model is used to estimate the casualties in Turkey, it can be easily trained with the data from the other countries and used for the estimation of the corresponding COVID-19 casualties.
dc.identifier.doi10.1109/ACCESS.2020.3033146
dc.identifier.endpage193906
dc.identifier.issn2169-3536
dc.identifier.pmid34976560
dc.identifier.scopus2-s2.0-85096033116
dc.identifier.scopusqualityQ1
dc.identifier.startpage193898
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2020.3033146
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2168
dc.identifier.volume8
dc.identifier.wosWOS:000587842700001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Access
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectCOVID-19
dc.subjectMathematical model
dc.subjectAnalytical models
dc.subjectPredictive models
dc.subjectViruses (medical)
dc.subjectParametric statistics
dc.subjectCOVID-19 casualties
dc.subjectparametric model
dc.subjectprediction
dc.subjectSpID model
dc.subjectSIR model
dc.titleA Novel Parametric Model for the Prediction and Analysis of the COVID-19 Casualties
dc.typeArticle

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