The COVID-19 pandemic in the African continent

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Abstract

In December 2019, a new coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and associated disease, coronavirus disease 2019 (COVID-19), was identified in China. This virus spread quickly and in March, 2020, it was declared a pandemic. Scientists predicted the worst scenario to occur in Africa since it was the least developed of the continents in terms of human development index, lagged behind others in achievement of the United Nations sustainable development goals (SDGs), has inadequate resources for provision of social services, and has many fragile states. In addition, there were relatively few research reporting findings on COVID-19 in Africa. On the contrary, the more developed countries reported higher disease incidences and mortality rates. However, for Africa, the earlier predictions and modelling into COVID-19 incidence and mortality did not fit into the reality. Therefore, the main objective of this forum is to bring together infectious diseases and public health experts to give an overview of COVID-19 in Africa and share their thoughts and opinions on why Africa behaved the way it did. Furthermore, the experts highlight what needs to be done to support Africa to consolidate the status quo and overcome the negative effects of COVID-19 so as to accelerate attainment of the SDGs.

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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

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Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation

Daniel Wrapp, Nianshuang Wang, Kizzmekia S. Corbett … (2020)

Structure of the nCoV trimeric spike The World Health Organization has declared the outbreak of a novel coronavirus (2019-nCoV) to be a public health emergency of international concern. The virus binds to host cells through its trimeric spike glycoprotein, making this protein a key target for potential therapies and diagnostics. Wrapp et al. determined a 3.5-angstrom-resolution structure of the 2019-nCoV trimeric spike protein by cryo–electron microscopy. Using biophysical assays, the authors show that this protein binds at least 10 times more tightly than the corresponding spike protein of severe acute respiratory syndrome (SARS)–CoV to their common host cell receptor. They also tested three antibodies known to bind to the SARS-CoV spike protein but did not detect binding to the 2019-nCoV spike protein. These studies provide valuable information to guide the development of medical counter-measures for 2019-nCoV. Science, this issue p. 1260

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Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals

Alba Grifoni, Daniela Weiskopf, Sydney Ramirez … (2020)

Summary Understanding adaptive immunity to SARS-CoV-2 is important for vaccine development, interpreting coronavirus disease 2019 (COVID-19) pathogenesis, and calibration of pandemic control measures. Using HLA class I and II predicted peptide ‘megapools’, circulating SARS-CoV-2−specific CD8+ and CD4+ T cells were identified in ∼70% and 100% of COVID-19 convalescent patients, respectively. CD4+ T cell responses to spike, the main target of most vaccine efforts, were robust and correlated with the magnitude of the anti-SARS-CoV-2 IgG and IgA titers. The M, spike and N proteins each accounted for 11-27% of the total CD4+ response, with additional responses commonly targeting nsp3, nsp4, ORF3a and ORF8, among others. For CD8+ T cells, spike and M were recognized, with at least eight SARS-CoV-2 ORFs targeted. Importantly, we detected SARS-CoV-2−reactive CD4+ T cells in ∼40-60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating ‘common cold’ coronaviruses and SARS-CoV-2.

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Author and article information

Contributors

Godfrey Bwire:

ORCID: http://orcid.org/0000-0002-8376-2857

gbwire1@yahoo.com , gbwire@musph.ac.ug

Alex Riolexus Ario:

ORCID: http://orcid.org/0000-0002-3560-1952

riolexus@uniph.go.ug

Patricia Eyu: patricia.eyu@musph.ac.ug

Felix Ocom: felixocom@gmail.com

Joseph F. Wamala: josephwamala@gmail.com , j_wamala@yahoo.com , wamalaj@who.int

Kwadwo A. Kusi:

ORCID: http://orcid.org/0000-0001-5483-9985

Akusi@noguchi.ug.edu.gh , kusi.asamoah@gmail.com

Latif Ndeketa:

ORCID: http://orcid.org/0000-0002-3376-597X

lndeketa@mlw.mw , latif.ndeketa@lstmed.ac.uk

Kondwani C. Jambo:

ORCID: http://orcid.org/0000-0002-3195-2210

Kondwani.jambo@lstmed.ac.uk , kjambo@mlw.mw

Rhoda K. Wanyenze: rwanyenze@musph.ac.ug

Ambrose O. Talisuna: talisunaa@who.int

Journal

Journal ID (nlm-ta): BMC Med

Journal ID (iso-abbrev): BMC Med

Title: BMC Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1741-7015

Publication date (Electronic): 2 May 2022

Publication date PMC-release: 2 May 2022

Publication date Collection: 2022

Volume: 20

Electronic Location Identifier: 167

Affiliations

[1 ]GRID grid.415705.2, Department of Integrated Epidemiology Surveillance and Public Health Emergencies, , Ministry of Health, ; P.O Box 7272, Kampala, Uganda

[2 ]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, School of Public Health, , Makerere University, ; P.O. Box 7072, Kampala, Uganda

[3 ]Uganda National Institute of Public Health, Kampala, Uganda

[4 ]World Health Organization (WHO), Juba, South Sudan

[5 ]GRID grid.8652.9, ISNI 0000 0004 1937 1485, Noguchi Memorial Institute for Medical Research, College of Health Sciences, , University of Ghana, ; Accra, Ghana

[6 ]GRID grid.419393.5, ISNI 0000 0004 8340 2442, Malawi-Liverpool-Wellcome Programme (MLW), ; Blantyre, Malawi

[7 ]GRID grid.48004.38, ISNI 0000 0004 1936 9764, Liverpool School of Tropical Medicine, ; Liverpool, UK

[8 ]GRID grid.463718.f, ISNI 0000 0004 0639 2906, Epidemic Preparedness and Response Cluster, World Health Organization, Regional Office for Africa, ; Brazzaville, Congo

Author information

Godfrey Bwire http://orcid.org/0000-0002-8376-2857

Alex Riolexus Ario http://orcid.org/0000-0002-3560-1952

Kwadwo A. Kusi http://orcid.org/0000-0001-5483-9985

Latif Ndeketa http://orcid.org/0000-0002-3376-597X

Kondwani C. Jambo http://orcid.org/0000-0002-3195-2210

Article

Publisher ID: 2367

DOI: 10.1186/s12916-022-02367-4

PMC ID: 9059455

PubMed ID: 35501853

SO-VID: eab5400d-43fd-48f0-9aeb-12de5da3a7bf

License:

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 5 April 2022

Date accepted : 5 April 2022

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ScienceOpen disciplines: Medicine

Keywords: covid,africa,pandemic,infectious disease,health,epidemiology,coronavirus,vaccination,coverage,immunity,essential health services

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ScienceOpen disciplines: Medicine

Keywords: covid, africa, pandemic, infectious disease, health, epidemiology, coronavirus, vaccination, coverage, immunity, essential health services

The COVID-19 pandemic in the African continent

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Novel Coronavirus Disease COVID-19

Most cited references 101

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation

Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals

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