Relationship between COVID-19 and Community Mobility: Sample from Malatya Province

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dc.contributor.authorYılancı, Veli
dc.contributor.authorAkbulut, Ahmet Sami
dc.contributor.author, Ali
dc.contributor.authorİşlek, Hüseyin
dc.contributor.authorZeren, Fatma
dc.contributor.authorBentli, Recep
dc.date.accessioned2024-08-04T19:53:21Z
dc.date.available2024-08-04T19:53:21Z
dc.date.issued2022
dc.departmentİnönü Üniversitesien_US
dc.description.abstractAfter 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.en_US
dc.identifier.doi10.5455/medscience.2022.07.159
dc.identifier.endpage1326en_US
dc.identifier.issn2147-0634
dc.identifier.issue3en_US
dc.identifier.startpage1322en_US
dc.identifier.trdizinid1131399en_US
dc.identifier.urihttps://doi.org/10.5455/medscience.2022.07.159
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/1131399
dc.identifier.urihttps://hdl.handle.net/11616/89692
dc.identifier.volume11en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofMedicine Scienceen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleRelationship between COVID-19 and Community Mobility: Sample from Malatya Provinceen_US
dc.typeArticleen_US

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