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Analysis of Spatiotemporal Pattern for COVID‐19 in Algeria Using Space‐Time-Cubes
(*) Corresponding author
DOI: https://doi.org/10.15866/iremos.v15i1.21282
Abstract
This study aims to analyze the spatiotemporal models of the 2019 coronavirus pandemic (SARS CoV-2) in Algeria and to identify the distribution and spatiotemporal evolution characteristics of the pandemic. Thus, space-time cubes were used to analyze the local outliers, spatiotemporal clustering models and the trends of cold spots and hotspots of the SARS CoV-2 cases. This study has concluded that the pandemic, at first, has spread slowly in northern Algeria, and then has accelerated quickly to affect the whole country, before slowing down and stabilizing. In addition, the results of the outliers analysis has suggested that the pandemic had a high clustering pattern during the studied period, and the Low-Low outlier has been the main spatiotemporal clustering pattern, which indicates that the pandemic situation has remained at a relatively low level in general. In addition, the analysis of emerging hotspots has helped to detect different types of hotspots in the northern areas of Algeria and different types of cold spots in the far south and in the center of the country. Finally, the use of spatiotemporal analysis based on space time cubes can determine the different spatiotemporal models of SARS CoV-2 data.
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