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Spatiotemporal pattern of Covid-19 outbreak in Turkey

The earliest case of Covid-19 was documented in Wuhan city of China and since then the virus has been spreading throughout the globe. The aim of this study is to evaluate the clusters of Covid-19 among the provinces in Turkey and to examine whether the clustering pattern has changed after the countr...

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Autores principales: Aral, Neşe, Bakır, Hasan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200931/
https://www.ncbi.nlm.nih.gov/pubmed/35729953
http://dx.doi.org/10.1007/s10708-022-10666-9
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author Aral, Neşe
Bakır, Hasan
author_facet Aral, Neşe
Bakır, Hasan
author_sort Aral, Neşe
collection PubMed
description The earliest case of Covid-19 was documented in Wuhan city of China and since then the virus has been spreading throughout the globe. The aim of this study is to evaluate the clusters of Covid-19 among the provinces in Turkey and to examine whether the clustering pattern has changed after the country’s lockdown strategy. The spatial dependence of Covid-19 in 81 provinces of Turkey was examined by spatial analysis between February 8 and June 28, 2021. Global and Local Moran's I and Gi* were employed to measure the global and local spatial autocorrelation degrees. The geographical distribution of Covid-19 in the provinces of Turkey showed a strong spatial autocorrelation while the spatial structure of the clusters varied by weeks. The findings of the study show that the complete lockdown carried out in Turkey has been quite effective in mitigating Covid-19. The importance of spatial relations in preventing the spread of the disease in Turkey has also been demonstrated in this context.
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spelling pubmed-92009312022-06-17 Spatiotemporal pattern of Covid-19 outbreak in Turkey Aral, Neşe Bakır, Hasan GeoJournal Article The earliest case of Covid-19 was documented in Wuhan city of China and since then the virus has been spreading throughout the globe. The aim of this study is to evaluate the clusters of Covid-19 among the provinces in Turkey and to examine whether the clustering pattern has changed after the country’s lockdown strategy. The spatial dependence of Covid-19 in 81 provinces of Turkey was examined by spatial analysis between February 8 and June 28, 2021. Global and Local Moran's I and Gi* were employed to measure the global and local spatial autocorrelation degrees. The geographical distribution of Covid-19 in the provinces of Turkey showed a strong spatial autocorrelation while the spatial structure of the clusters varied by weeks. The findings of the study show that the complete lockdown carried out in Turkey has been quite effective in mitigating Covid-19. The importance of spatial relations in preventing the spread of the disease in Turkey has also been demonstrated in this context. Springer Netherlands 2022-06-16 2023 /pmc/articles/PMC9200931/ /pubmed/35729953 http://dx.doi.org/10.1007/s10708-022-10666-9 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Aral, Neşe
Bakır, Hasan
Spatiotemporal pattern of Covid-19 outbreak in Turkey
title Spatiotemporal pattern of Covid-19 outbreak in Turkey
title_full Spatiotemporal pattern of Covid-19 outbreak in Turkey
title_fullStr Spatiotemporal pattern of Covid-19 outbreak in Turkey
title_full_unstemmed Spatiotemporal pattern of Covid-19 outbreak in Turkey
title_short Spatiotemporal pattern of Covid-19 outbreak in Turkey
title_sort spatiotemporal pattern of covid-19 outbreak in turkey
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200931/
https://www.ncbi.nlm.nih.gov/pubmed/35729953
http://dx.doi.org/10.1007/s10708-022-10666-9
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