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Communication

COVID-19 Global Risk: Expectation vs. Reality

1
School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney 2116, Australia
2
College of Information Technology, UAE University, Al-Ain, UAE
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2020, 17(15), 5592; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17155592
Received: 8 June 2020 / Revised: 24 July 2020 / Accepted: 25 July 2020 / Published: 3 August 2020
(This article belongs to the Special Issue Feature Papers in Public Health Statistics and Risk Assessment)
Background and Objective: COVID-19 has engulfed the entire world, with many countries struggling to contain the pandemic. In order to understand how each country is impacted by the virus compared with what would have been expected prior to the pandemic and the mortality risk on a global scale, a multi-factor weighted spatial analysis is presented. Method: A number of key developmental indicators across three main categories of demographics, economy, and health infrastructure were used, supplemented with a range of dynamic indicators associated with COVID-19 as independent variables. Using normalised COVID-19 mortality on 13 May 2020 as a dependent variable, a linear regression (N = 153 countries) was performed to assess the predictive power of the various indicators. Results: The results of the assessment show that when in combination, dynamic and static indicators have higher predictive power to explain risk variation in COVID-19 mortality compared with static indicators alone. Furthermore, as of 13 May 2020 most countries were at a similar or lower risk level than what would have been expected pre-COVID, with only 44/153 countries experiencing a more than 20% increase in mortality risk. The ratio of elderly emerges as a strong predictor but it would be worthwhile to consider it in light of the family makeup of individual countries. Conclusion: In conclusion, future avenues of data acquisition related to COVID-19 are suggested. The paper concludes by discussing the ability of various factors to explain COVID-19 mortality risk. The ratio of elderly in combination with the dynamic variables associated with COVID-19 emerge as more significant risk predictors in comparison to socio-economic and demographic indicators. View Full-Text
Keywords: COVID-19; risk evaluation; multi-weighted factor analysis COVID-19; risk evaluation; multi-weighted factor analysis
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MDPI and ACS Style

Arsalan, M.; Mubin, O.; Alnajjar, F.; Alsinglawi, B. COVID-19 Global Risk: Expectation vs. Reality. Int. J. Environ. Res. Public Health 2020, 17, 5592. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17155592

AMA Style

Arsalan M, Mubin O, Alnajjar F, Alsinglawi B. COVID-19 Global Risk: Expectation vs. Reality. International Journal of Environmental Research and Public Health. 2020; 17(15):5592. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17155592

Chicago/Turabian Style

Arsalan, Mudassar, Omar Mubin, Fady Alnajjar, and Belal Alsinglawi. 2020. "COVID-19 Global Risk: Expectation vs. Reality" International Journal of Environmental Research and Public Health 17, no. 15: 5592. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17155592

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