GIS-based spatial analysis and hotspot detection of COVID-۱۹ outbreak

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نوع سند: مقاله کنفرانسی
زبان: English
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NGTU02_010

تاریخ نمایه سازی: 12 مرداد 1400

Abstract:

Coronavirus disease (COVID-۱۹), caused by acute respiratory syndrome coronavirus-۲ (SARS-CoV-۲), has become a global crisis due to its severe epidemiological characteristics, which was reported in Wuhan, China, in December ۲۰۱۹. In this study, we calculated the COVID-۱۹ cumulative incidence rate (CIR) and cumulative fatality rate (CFR) for each country throughout the world from the first day of the outbreak by January ۹, ۲۰۲۱. We analysed the spatial patterns of COVID-۱۹ using Global Moran’s I analysis. Further, Hot Spot analysis (Getis-Ord Gi*) was implemented to investigate high-risk and low-risk clusters of COVID-۱۹ globally. Yemen, Mexico, and Ecuador had the highest CFR rates among others. In terms of CIR, the highest values belonged to Andorra, Gibraltar (United Kingdom), and Montenegro at the time of the study. Spatial distribution of CIR values for all countries showed an intense clustered pattern. Results of Hot Spot analysis revealed that almost all parts of Europe, especially eastern, western, and southern countries were intensely infected and high-risk areas in terms of COVID-۱۹ spread. United States was the other mostly infected country demonstrating the confidence level of ۹۹%. Besides, countries located in Africa presented the lowest CIR levels, which made them cold spot areas. In conclusion, Applying spatial analysis could be beneficial due to its applicability in illustrating the high-risk locations of disease and providing useful information for principals to implement specific interventions in regions with different levels of risks.

Authors

Nima Kianfar

Department of GIS, Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran, Iran

Aliasghar Azma

College of Architecture and Civil engineering, Beijing University of Technology, Beijing, China

Mohammad Saadi Mesgari

Department of GIS, Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran, Iran