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Predictors of COVID-19 epidemics in countries of the World Health Organization African Region
Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the fir...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604723/ https://www.ncbi.nlm.nih.gov/pubmed/34480125 http://dx.doi.org/10.1038/s41591-021-01491-7 |
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author | Zhang, Feifei Karamagi, Humphrey Nsenga, Ngoy Nanyunja, Miriam Karinja, Miriam Amanfo, Seth Chase-Topping, Margo Calder-Gerver, Giles McGibbon, Miles Huber, Alexandra Wagner-Gamble, Tara Guo, Chuan-Guo Haynes, Samuel Morrison, Alistair Ferguson, Miranda Awandare, Gordon A. Mutapi, Francisca Yoti, Zabulon Cabore, Joseph Moeti, Matshidiso R. Woolhouse, Mark E. J. |
author_facet | Zhang, Feifei Karamagi, Humphrey Nsenga, Ngoy Nanyunja, Miriam Karinja, Miriam Amanfo, Seth Chase-Topping, Margo Calder-Gerver, Giles McGibbon, Miles Huber, Alexandra Wagner-Gamble, Tara Guo, Chuan-Guo Haynes, Samuel Morrison, Alistair Ferguson, Miranda Awandare, Gordon A. Mutapi, Francisca Yoti, Zabulon Cabore, Joseph Moeti, Matshidiso R. Woolhouse, Mark E. J. |
author_sort | Zhang, Feifei |
collection | PubMed |
description | Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning. |
format | Online Article Text |
id | pubmed-8604723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-86047232021-12-03 Predictors of COVID-19 epidemics in countries of the World Health Organization African Region Zhang, Feifei Karamagi, Humphrey Nsenga, Ngoy Nanyunja, Miriam Karinja, Miriam Amanfo, Seth Chase-Topping, Margo Calder-Gerver, Giles McGibbon, Miles Huber, Alexandra Wagner-Gamble, Tara Guo, Chuan-Guo Haynes, Samuel Morrison, Alistair Ferguson, Miranda Awandare, Gordon A. Mutapi, Francisca Yoti, Zabulon Cabore, Joseph Moeti, Matshidiso R. Woolhouse, Mark E. J. Nat Med Article Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning. Nature Publishing Group US 2021-09-03 2021 /pmc/articles/PMC8604723/ /pubmed/34480125 http://dx.doi.org/10.1038/s41591-021-01491-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zhang, Feifei Karamagi, Humphrey Nsenga, Ngoy Nanyunja, Miriam Karinja, Miriam Amanfo, Seth Chase-Topping, Margo Calder-Gerver, Giles McGibbon, Miles Huber, Alexandra Wagner-Gamble, Tara Guo, Chuan-Guo Haynes, Samuel Morrison, Alistair Ferguson, Miranda Awandare, Gordon A. Mutapi, Francisca Yoti, Zabulon Cabore, Joseph Moeti, Matshidiso R. Woolhouse, Mark E. J. Predictors of COVID-19 epidemics in countries of the World Health Organization African Region |
title | Predictors of COVID-19 epidemics in countries of the World Health Organization African Region |
title_full | Predictors of COVID-19 epidemics in countries of the World Health Organization African Region |
title_fullStr | Predictors of COVID-19 epidemics in countries of the World Health Organization African Region |
title_full_unstemmed | Predictors of COVID-19 epidemics in countries of the World Health Organization African Region |
title_short | Predictors of COVID-19 epidemics in countries of the World Health Organization African Region |
title_sort | predictors of covid-19 epidemics in countries of the world health organization african region |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604723/ https://www.ncbi.nlm.nih.gov/pubmed/34480125 http://dx.doi.org/10.1038/s41591-021-01491-7 |
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