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COVID-19 Global Risk: Expectation vs. Reality

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 mul...

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Autores principales: Arsalan, Mudassar, Mubin, Omar, Alnajjar, Fady, Alsinglawi, Belal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432363/
https://www.ncbi.nlm.nih.gov/pubmed/32756513
http://dx.doi.org/10.3390/ijerph17155592
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author Arsalan, Mudassar
Mubin, Omar
Alnajjar, Fady
Alsinglawi, Belal
author_facet Arsalan, Mudassar
Mubin, Omar
Alnajjar, Fady
Alsinglawi, Belal
author_sort Arsalan, Mudassar
collection PubMed
description 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.
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spelling pubmed-74323632020-08-24 COVID-19 Global Risk: Expectation vs. Reality Arsalan, Mudassar Mubin, Omar Alnajjar, Fady Alsinglawi, Belal Int J Environ Res Public Health Communication 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. MDPI 2020-08-03 2020-08 /pmc/articles/PMC7432363/ /pubmed/32756513 http://dx.doi.org/10.3390/ijerph17155592 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Arsalan, Mudassar
Mubin, Omar
Alnajjar, Fady
Alsinglawi, Belal
COVID-19 Global Risk: Expectation vs. Reality
title COVID-19 Global Risk: Expectation vs. Reality
title_full COVID-19 Global Risk: Expectation vs. Reality
title_fullStr COVID-19 Global Risk: Expectation vs. Reality
title_full_unstemmed COVID-19 Global Risk: Expectation vs. Reality
title_short COVID-19 Global Risk: Expectation vs. Reality
title_sort covid-19 global risk: expectation vs. reality
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432363/
https://www.ncbi.nlm.nih.gov/pubmed/32756513
http://dx.doi.org/10.3390/ijerph17155592
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