Çanakkale Onsekiz Mart Üniversitesi
Siyasal Bilgiler Fakültesi
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Prof. Dr. Veli Yılancı'nın makalesi TRDizin'de endekslenen Medicine Science adlı dergide yayınlandı

Prof. Dr. Veli Yılancı'nın "Relationship between COVID-19 and Community Mobility: Sample from Malatya Province" başlıklı makalesi TRDizin'de endekslenen International Journal of Managerial Finance adlı dergide yayınlandı.

 

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After the WHO defined the COVID-19 as a pandemic on March 11, 2020, measures such as wearing masks, keeping social distance, and staying at home were taken to reduce transmission worldwide. Community mobility is one of the important factors contributing to the uncontrolled spread of the epidemic. The aim of the study is to examine the relationship between the number of COVID-19 cases in the first half of 2021 in Türkiye’s Malatya province and Google community mobility reports. The number of COVID-19 cases in Malatya between 01 January 2021 and 31 May 2021 was obtained from the Malatya Provincial Health Directorate. Community mobility data in the relevant period was obtained from Google community mobility. To examine the relationship between the number of COVID-19 cases and community mobility, wavelet coherence analysis was used. The Google mobility data used in the study consists of six different categories covering markets and pharmacies, parks, residential, retail, and recreational areas, public transport stops and workplaces. According to the results of wavelet coherence analysis, the increase in mobility in markets and pharmacies, retail and recreation areas, parks, workplaces, and transportation stations has increased the number of COVID-19 cases. The direction of the relationship between COVID-19 and residential mobility was found to be negative. In other words, the increase in the time spent in residences leads to a decrease in the number of COVID-19 cases. According to the results of wavelet coherence analysis, it was observed that in five of the six categories included in the study, there was a significant relationship between the number of cases and these categories, for the period examined at various frequencies. Depending on the degree of interactions at short- and long-term frequencies covered in the study, policy makers can determine short- and long-term policies to direct human mobility and thereby control the pandemic.