Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa
IntroductionThe coronavirus disease 2019 (COVID-19) pandemic has caused significant public health and socioeconomic crises across Africa; however, the prevalent patterns of COVID-19 and the circulating characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in the co...
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Frontiers Media S.A.
2025-02-01
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1526727/full |
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| author | Li-Ping Gao Can-Jun Zheng Ting-Ting Tian Alie Brima Tia Michael K. Abdulai Kang Xiao Cao Chen Dong-Lin Liang Qi Shi Zhi-Guo Liu Xiao-Ping Dong Xiao-Ping Dong |
| author_facet | Li-Ping Gao Can-Jun Zheng Ting-Ting Tian Alie Brima Tia Michael K. Abdulai Kang Xiao Cao Chen Dong-Lin Liang Qi Shi Zhi-Guo Liu Xiao-Ping Dong Xiao-Ping Dong |
| author_sort | Li-Ping Gao |
| collection | DOAJ |
| description | IntroductionThe coronavirus disease 2019 (COVID-19) pandemic has caused significant public health and socioeconomic crises across Africa; however, the prevalent patterns of COVID-19 and the circulating characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in the continent remain insufficiently documented.MethodsIn this study, national data on case numbers, infection incidences, mortality rates, the circulation of SARS-CoV-2 variants, and key health indexes were collected from various official and professional sources between January 2020 and December 2023 were analyzed with SaTScan and geographically weighted regression (GWR).ResultsThe prevalent profiles and circulating features of SARS-CoV-2 across the African continent, including its five regions and all African countries, were analyzed. Four major waves of the epidemic were observed. The first wave was closely associated with the introduction of the early SARS-CoV-2 strain while the subsequent waves were linked to the emergence of specific variants, including variants of concern (VOCs) Alpha, Beta, variants of interest (VOIs) Eta (second wave), VOC Delta (third wave), and VOC Omicron (fourth wave). SaTScan analysis identified four large spatiotemporal clusters that affected various countries. A significant number of countries (50 out of 56) reported their first cases during February 2020 and March 2020, predominantly involving individuals with confirmed cross-continental travel histories, mainly from Europe. In total, 12 distinct SARS-CoV-2 VOCs and VOIs were identified, with the most prevalent being VOCs Omicron, Delta, Beta, Alpha, and VOI Eta. Unlike the dominance of VOC Delta during the third wave and Omicron during the fourth wave, VOC Alpha was relatively rare in the Southern regions but more common in the other four regions. At the same time, Beta predominated in the Southern region and Eta in the Western region during the second wave. Additionally, relatively higher COVID-19 case incidences and mortalities were reported in the Southern and Northern African regions. Spearman rank correlation and geographically weighted regression (GWR) analyses of COVID-19 incidences against health indexes in 52 African countries indicate that countries with higher national health expenditures and better personnel indexes tended to report higher case incidences.DiscussionThis study offers a detailed overview of the COVID-19 pandemic in Africa. Strengthening the capacity of health institutions across African countries is essential for the timely detection of new SARS-CoV-2 variants and, consequently, for preparedness against future COVID-19 pandemics and other potentially infectious disease outbreaks. |
| format | Article |
| id | doaj-art-e94908ba7aaf4d449af3d9da0393c631 |
| institution | OA Journals |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-e94908ba7aaf4d449af3d9da0393c6312025-08-20T02:14:27ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-02-011310.3389/fpubh.2025.15267271526727Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in AfricaLi-Ping Gao0Can-Jun Zheng1Ting-Ting Tian2Alie Brima Tia3Michael K. Abdulai4Kang Xiao5Cao Chen6Dong-Lin Liang7Qi Shi8Zhi-Guo Liu9Xiao-Ping Dong10Xiao-Ping Dong11National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaChinese Center for Disease Control and Prevention, Beijing, ChinaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaSierra Leone-China Friendship Biological Safety Laboratory, Freetown, Sierra LeoneSierra Leone-China Friendship Biological Safety Laboratory, Freetown, Sierra LeoneNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaShanghai Institute of Infectious Disease and Biosafety, Shanghai, ChinaIntroductionThe coronavirus disease 2019 (COVID-19) pandemic has caused significant public health and socioeconomic crises across Africa; however, the prevalent patterns of COVID-19 and the circulating characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in the continent remain insufficiently documented.MethodsIn this study, national data on case numbers, infection incidences, mortality rates, the circulation of SARS-CoV-2 variants, and key health indexes were collected from various official and professional sources between January 2020 and December 2023 were analyzed with SaTScan and geographically weighted regression (GWR).ResultsThe prevalent profiles and circulating features of SARS-CoV-2 across the African continent, including its five regions and all African countries, were analyzed. Four major waves of the epidemic were observed. The first wave was closely associated with the introduction of the early SARS-CoV-2 strain while the subsequent waves were linked to the emergence of specific variants, including variants of concern (VOCs) Alpha, Beta, variants of interest (VOIs) Eta (second wave), VOC Delta (third wave), and VOC Omicron (fourth wave). SaTScan analysis identified four large spatiotemporal clusters that affected various countries. A significant number of countries (50 out of 56) reported their first cases during February 2020 and March 2020, predominantly involving individuals with confirmed cross-continental travel histories, mainly from Europe. In total, 12 distinct SARS-CoV-2 VOCs and VOIs were identified, with the most prevalent being VOCs Omicron, Delta, Beta, Alpha, and VOI Eta. Unlike the dominance of VOC Delta during the third wave and Omicron during the fourth wave, VOC Alpha was relatively rare in the Southern regions but more common in the other four regions. At the same time, Beta predominated in the Southern region and Eta in the Western region during the second wave. Additionally, relatively higher COVID-19 case incidences and mortalities were reported in the Southern and Northern African regions. Spearman rank correlation and geographically weighted regression (GWR) analyses of COVID-19 incidences against health indexes in 52 African countries indicate that countries with higher national health expenditures and better personnel indexes tended to report higher case incidences.DiscussionThis study offers a detailed overview of the COVID-19 pandemic in Africa. Strengthening the capacity of health institutions across African countries is essential for the timely detection of new SARS-CoV-2 variants and, consequently, for preparedness against future COVID-19 pandemics and other potentially infectious disease outbreaks.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1526727/fullCOVID-19SARS-CoV-2varianthealth indexesAfrica |
| spellingShingle | Li-Ping Gao Can-Jun Zheng Ting-Ting Tian Alie Brima Tia Michael K. Abdulai Kang Xiao Cao Chen Dong-Lin Liang Qi Shi Zhi-Guo Liu Xiao-Ping Dong Xiao-Ping Dong Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa Frontiers in Public Health COVID-19 SARS-CoV-2 variant health indexes Africa |
| title | Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa |
| title_full | Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa |
| title_fullStr | Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa |
| title_full_unstemmed | Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa |
| title_short | Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa |
| title_sort | spatiotemporal prevalence of covid 19 and sars cov 2 variants in africa |
| topic | COVID-19 SARS-CoV-2 variant health indexes Africa |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1526727/full |
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