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Main modulators of COVID-19 epidemic in sub-Saharan Africa

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is responsible for an important global death toll from which sub-Saharan Africa (SSA) seems mostly protected. The reasons explaining this situation are still poorly understood. METHODS: We analyzed the correlation between reported COVID-19...

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Autores principales: Zinsou, Boris-Enock, Letourneur, Diane, Siko, Joël, de Souza, Raïssa Muriel, Adjagba, Frejus, Pineau, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797222/
https://www.ncbi.nlm.nih.gov/pubmed/36594042
http://dx.doi.org/10.1016/j.heliyon.2022.e12727
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author Zinsou, Boris-Enock
Letourneur, Diane
Siko, Joël
de Souza, Raïssa Muriel
Adjagba, Frejus
Pineau, Pascal
author_facet Zinsou, Boris-Enock
Letourneur, Diane
Siko, Joël
de Souza, Raïssa Muriel
Adjagba, Frejus
Pineau, Pascal
author_sort Zinsou, Boris-Enock
collection PubMed
description BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is responsible for an important global death toll from which sub-Saharan Africa (SSA) seems mostly protected. The reasons explaining this situation are still poorly understood. METHODS: We analyzed the correlation between reported COVID-19 data between February 14, 2020 and May 18, 2021, and demographic, socioeconomic, climatic, diagnostic data, and comorbidities in 47 SSA countries. Different databases including the WHO data center, Our World in Data, and the World Bank were used. FINDINGS: As of May 17, 2021, SSA reported 2% of COVID-19 cases and 2.9% of deaths, with the southern region being the most affected with 56.4% of cases and 75.0% of deaths. COVID-19 mortality was positively correlated with medical variables (national obesity rate, diabetes prevalence, cancer incidence, and cardiovascular disease mortality rate), socioeconomic characteristics (international tourism, per capita health expenditure, human development index, HDI, and years of schooling), and health system variables (nurse density, number of COVID-19 tests per capita), but negatively correlated with the population under 15 years of age and the malaria index. INTERPRETATION: Our study suggests that higher economic status fits with high COVID-19 mortality in SSA. In this regard, it represents primarily a disease of modern and wealthy societies, and can therefore be considered as an exception among infectious diseases that historically affected more severely underserved populations living in low- and middle-income countries. However, it should be made clear that observed correlations do not imply inevitably causation and that additional studies are necessary to confirm our observations.
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spelling pubmed-97972222022-12-29 Main modulators of COVID-19 epidemic in sub-Saharan Africa Zinsou, Boris-Enock Letourneur, Diane Siko, Joël de Souza, Raïssa Muriel Adjagba, Frejus Pineau, Pascal Heliyon Research Article BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is responsible for an important global death toll from which sub-Saharan Africa (SSA) seems mostly protected. The reasons explaining this situation are still poorly understood. METHODS: We analyzed the correlation between reported COVID-19 data between February 14, 2020 and May 18, 2021, and demographic, socioeconomic, climatic, diagnostic data, and comorbidities in 47 SSA countries. Different databases including the WHO data center, Our World in Data, and the World Bank were used. FINDINGS: As of May 17, 2021, SSA reported 2% of COVID-19 cases and 2.9% of deaths, with the southern region being the most affected with 56.4% of cases and 75.0% of deaths. COVID-19 mortality was positively correlated with medical variables (national obesity rate, diabetes prevalence, cancer incidence, and cardiovascular disease mortality rate), socioeconomic characteristics (international tourism, per capita health expenditure, human development index, HDI, and years of schooling), and health system variables (nurse density, number of COVID-19 tests per capita), but negatively correlated with the population under 15 years of age and the malaria index. INTERPRETATION: Our study suggests that higher economic status fits with high COVID-19 mortality in SSA. In this regard, it represents primarily a disease of modern and wealthy societies, and can therefore be considered as an exception among infectious diseases that historically affected more severely underserved populations living in low- and middle-income countries. However, it should be made clear that observed correlations do not imply inevitably causation and that additional studies are necessary to confirm our observations. Elsevier 2022-12-29 /pmc/articles/PMC9797222/ /pubmed/36594042 http://dx.doi.org/10.1016/j.heliyon.2022.e12727 Text en © 2022 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Zinsou, Boris-Enock
Letourneur, Diane
Siko, Joël
de Souza, Raïssa Muriel
Adjagba, Frejus
Pineau, Pascal
Main modulators of COVID-19 epidemic in sub-Saharan Africa
title Main modulators of COVID-19 epidemic in sub-Saharan Africa
title_full Main modulators of COVID-19 epidemic in sub-Saharan Africa
title_fullStr Main modulators of COVID-19 epidemic in sub-Saharan Africa
title_full_unstemmed Main modulators of COVID-19 epidemic in sub-Saharan Africa
title_short Main modulators of COVID-19 epidemic in sub-Saharan Africa
title_sort main modulators of covid-19 epidemic in sub-saharan africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797222/
https://www.ncbi.nlm.nih.gov/pubmed/36594042
http://dx.doi.org/10.1016/j.heliyon.2022.e12727
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