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Modelling spatial variations of novel coronavirus disease (COVID-19): evidence from a global perspective
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Modelling spatial variations of novel coronavirus disease (COVID-19): evidence from a global perspective
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Journal Article
Modelling spatial variations of novel coronavirus disease (COVID-19): evidence from a global perspective
2022
Overview
In late December 2019, strange pneumonia was detected in a seafood market in Wuhan, China which was later termed COVID-19 by the World Health Organization. At present, the virus has spread across 232 countries worldwide killing 2,409,011 as of 17 February 2021 (9:37 CET). Motivated by a recent dataset, knowledge gaps, surge in global cases, and the need to combat the virus spread, this study examined the relationship between COVID-19 confirmed cases and attributable deaths at the global and regional levels. We used a panel of 232 countries (further disaggregated into Africa-49, Americas-54, Eastern Mediterranean-23, Europe-61, Southeast Asia-10, and Western Pacific-35) from 03 January 2020 to 28 November 2020, and the instrumental variable generalized method of moment’s model (IV-GMM) for analysing the datasets. The results showed that COVID-19 confirmed cases at both the global and regional levels have a strong positive effect on deaths. Thus, the confirmed cases significantly increase attributable deaths at the global and regional levels. At the global level, a 1% increase in confirmed cases increases attributable deaths by 0.78%. Regionally, a 1% increase in confirmed cases increases attributable deaths by 0.65% in Africa, 0.90% in the Americas, 0.67% in the Eastern Mediterranean, 0.72% in Europe, 0.88% in Southeast Asia, and 0.52% in the Western Pacific. This study expands the understanding of the relationship between COVID-19 cases and deaths by using a global dataset and the instrumental variable generalized method of moment’s model (IV-GMM) for the analysis that addresses endogeneity and omitted variable issues.
Publisher
Springer Nature B.V
Subject
