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Analysing Spatial Patterns of the COVID-19 Outbreak in Turkey

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dc.contributor.author Zeren, Fatma
dc.date.accessioned 2022-10-27T13:20:08Z
dc.date.available 2022-10-27T13:20:08Z
dc.date.issued 2020
dc.identifier.citation zeren f, YILANCI V (2020). Analysing Spatial Patterns of the COVID-19 Outbreak in Turkey. Bingöl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi (Online), 4(2), 27 - 40. 10.33399/biibfad.789117 en_US
dc.identifier.uri https://search.trdizin.gov.tr/yayin/detay/431255/analysing-spatial-patterns-of-the-covid-19-outbreak-in-turkey
dc.identifier.uri http://hdl.handle.net/11616/85226
dc.description.abstract COVID-19 is first detected on 12 March 2020 in Turkey, and since that day more than 100 thousand people are infected. In this study, we aim to determine risky provinces in terms of COVID-19 outbreak and also explore the spatial dynamics of the outbreak in Turkey using province-level data. To analyze spatial patterns of COVID-19, we employ spatial dependence statistics Moran-I. Also, we employ Local Indicator Spatial Association-LISA to detect the hot-spots and cold-spots. Moran-I coefficient found as low and statistically significant that shows spatial interaction is not strong in the context of the whole country. Also using LISA, we found Düzce, Kocaeli, Ordu, Tekirdağ, and Trabzon as hot-spots for data period, which indicates these cities can be classified as risky in terms of COVID-19 outbreak. There are more spatial interaction with their neighbours cities. In terms of the COVID-19 variable, in hot-spot provinces and neighboring provinces of these provinces, measures should be intensified, and control should be increased. en_US
dc.language.iso eng en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.title Analysing Spatial Patterns of the COVID-19 Outbreak in Turkey en_US
dc.type article en_US
dc.relation.ispartof Bingöl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi (Online) en_US
dc.department İnönü Üniversitesi en_US


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