The Data Science Met with the COVID-19: Revealing the Most Critical Measures Taken for the COVID-19 Pandemic

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dc.authorid
dc.contributor.authorKabakuş, Abdullah Talha
dc.date.accessioned2021-12-01T18:23:35Z
dc.date.available2021-12-01T18:23:35Z
dc.date.issued2020
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractThe whole world has been fighting against the novel coronavirus 2019 (COVID-19) for months. Despite theadvances in medical sciences, more than 235,000 people have died so far. And, despite all the measures taken forit, more than 3 million people have become sick of the COVID-19. The measures taken for the COVID-19 varythrough countries. So, revealing the most critical measures is necessary for a better fight against both the COVID19 and possible similar pandemics in the future. To this end, an analysis of the worldwide measures, which weretaken so far, for the COVID-19 pandemic was proposed within this paper. Since it is still early days, for the bestof our knowledge, there does not exist a single dataset contains all the features utilized within this study. Therefore,a novel global dataset containing the data regarding the COVID-19 for 52 countries around the world wasconstructed by combining various datasets. Then, the feature importance techniques were employed to reveal theimportance of the utilized features which means revealing the most important measures taken for the COVID-19pandemic for our case. Within the analysis, four features were utilized, namely, the population density, the walkingmobility, the driving mobility, and the number of lockdown days. According to the experimental result, thepopulation density was found as the most important feature which means the most critical measure in terms ofincreasing the spread of the COVID-19 pandemic. The order of the importance of the other features was found asthe walking mobility, the driving mobility, and the number of lockdown days, respectively.en_US
dc.identifier.doi10.35377/saucis.03.03.771501
dc.identifier.endpage209en_US
dc.identifier.issn2636-8129
dc.identifier.issue3en_US
dc.identifier.startpage201en_US
dc.identifier.urihttps://doi.org/10.35377/saucis.03.03.771501
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TkRFeU1UWTRPQT09
dc.identifier.urihttps://hdl.handle.net/20.500.12684/9735
dc.identifier.volume3en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorKabakuş, Abdullah Talha
dc.language.isoenen_US
dc.relation.ispartofSakarya University Journal of Computer and Information Sciences (Online)en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subject[No Keywords]en_US
dc.titleThe Data Science Met with the COVID-19: Revealing the Most Critical Measures Taken for the COVID-19 Pandemicen_US
dc.typeArticleen_US

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