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• W3202169618 abstract "The Covid-19 pandemic continues to threaten public health around the world. Understanding the spatial dimension of this impact is very important in terms of controlling and reducing the spread of the pandemic. This study measures the spatial association of the Covid-19 outbreak in Turkey between February 8 and May 28, 2021 and reveals its spatiotemporal pattern. In this context, global and local spatial autocorrelation was used to determine whether there is a spatial association of Covid-19 infections, while the spatial regression model was employed to reveal the geographical relationship of the potential factors affecting the number of Covid-19 cases. As a result of the analyzes made in this context, it has been observed that there are spatial associations and distinct spatial clusters in Covid-19 cases at the provincial level in Turkey. The results of the spatial regression model showed that population density and elderly dependency ratio are very important in explaining the model of Covid-19 case numbers. Additionally, it has been revealed that Covid-19 is affected by the Covid-19 numbers of neighboring provinces, apart from the said explanatory variables. The findings of the study revealed that spatial analysis is helpful in understanding the spread of the pandemic in Turkey. It has been determined that geographical location is an important factor to be considered in the investigation of the factors affecting Covid-19." @default.
• W3202169618 created "2021-10-11" @default.
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• W3202169618 date "2022-01-01" @default.
• W3202169618 modified "2023-10-11" @default.
• W3202169618 title "Spatiotemporal Analysis of Covid-19 in Turkey" @default.
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• W3202169618 doi "https://doi.org/10.1016/j.scs.2021.103421" @default.
• W3202169618 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8497064" @default.
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• W3202169618 hasPublicationYear "2022" @default.
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