Assessment of Three Mathematical Prediction Models for Forecasting the COVID-19 Outbreak in Iran and Turkey

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dc.authoridNiazkar, Hamid Reza/0000-0002-6143-9979
dc.authoridTURKKAN, YUSUF ALPTEKIN/0000-0003-1542-0713
dc.authoridNiazkar, Majid/0000-0002-5022-1026
dc.contributor.authorNiazkar, Majid
dc.contributor.authorEryilmaz Turkkan, Gokcen
dc.contributor.authorNiazkar, Hamid Reza
dc.contributor.authorTurkkan, Yusuf Alptekin
dc.date.accessioned2024-10-04T18:48:20Z
dc.date.available2024-10-04T18:48:20Z
dc.date.issued2020
dc.departmentBayburt Üniversitesien_US
dc.description.abstractCOVID-19 pandemic has become a concern of every nation, and it is crucial to apply an estimation model with a favorably-high accuracy to provide an accurate perspective of the situation. In this study, three explicit mathematical prediction models were applied to forecast the COVID-19 outbreak in Iran and Turkey. These models include a recursive-based method, Boltzmann Function-based model and Beesham's prediction model. These models were exploited to analyze the confirmed and death cases of the first 106 and 87 days of the COVID-19 outbreak in Iran and Turkey, respectively. This application indicates that the three models fail to predict the first 10 to 20 days of data, depending on the prediction model. On the other hand, the results obtained for the rest of the data demonstrate that the three prediction models achieve high values for the determination coefficient, whereas they yielded to different average absolute relative errors. Based on the comparison, the recursive-based model performs the best, while it estimated the COVID-19 outbreak in Iran better than that of in Turkey. Impacts of applying or relaxing control measurements like curfew in Turkey and reopening the low-risk businesses in Iran were investigated through the recursive-based model. Finally, the results demonstrate the merit of the recursive-based model in analyzing various scenarios, which may provide suitable information for health politicians and public health decision-makers.en_US
dc.identifier.doi10.1155/2020/7056285
dc.identifier.issn1748-670X
dc.identifier.issn1748-6718
dc.identifier.pmid33299466en_US
dc.identifier.scopus2-s2.0-85096959294en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1155/2020/7056285
dc.identifier.urihttp://hdl.handle.net/20.500.12403/3023
dc.identifier.volume2020en_US
dc.identifier.wosWOS:000597943600001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherHindawi Ltden_US
dc.relation.ispartofComputational and Mathematical Methods in Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleAssessment of Three Mathematical Prediction Models for Forecasting the COVID-19 Outbreak in Iran and Turkeyen_US
dc.typeArticleen_US

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