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

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dc.contributor.authorKabakuş, Abdullah Talha
dc.date.accessioned2025-10-11T20:42:17Z
dc.date.available2025-10-11T20:42:17Z
dc.date.issued2020
dc.departmentDüzce Üniversitesien_US
dc.description.abstractThe whole world has been fighting against the novel coronavirus 2019 (COVID-19) for months. Despite the advances in medical sciences, more than 235,000 people have died so far. And, despite all the measures taken for it, more than 3 million people have become sick of the COVID-19. The measures taken for the COVID-19 vary through countries. So, revealing the most critical measures is necessary for a better fight against both the COVID-19 and possible similar pandemics in the future. To this end, an analysis of the worldwide measures, which were taken so far, for the COVID-19 pandemic was proposed within this paper. Since it is still early days, for the best of 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 was constructed by combining various datasets. Then, the feature importance techniques were employed to reveal the importance of the utilized features which means revealing the most important measures taken for the COVID-19 pandemic for our case. Within the analysis, four features were utilized, namely, the population density, the walking mobility, the driving mobility, and the number of lockdown days. According to the experimental result, the population density was found as the most important feature which means the most critical measure in terms of increasing the spread of the COVID-19 pandemic. The order of the importance of the other features was found as the 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://hdl.handle.net/20.500.12684/20917
dc.identifier.volume3en_US
dc.institutionauthorKabakuş, Abdullah Talha
dc.language.isoenen_US
dc.publisherSakarya Universityen_US
dc.relation.ispartofSakarya University Journal of Computer and Information Sciencesen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKA_DergiPark_20250911
dc.subjectArtificial Intelligenceen_US
dc.subjectYapay Zekaen_US
dc.titleThe Data Science Met with the COVID-19: Revealing the Most Critical Measures Taken for the COVID-19 Pandemicen_US
dc.typeResearch Articleen_US

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