Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya.

Ifedayo MO Adetifa ORCID logo; Sophie Uyoga ORCID logo; John N Gitonga; Daisy Mugo; Mark Otiende ORCID logo; James Nyagwange; Henry K Karanja; James Tuju; Perpetual Wanjiku; Rashid Aman; +25 more... Mercy Mwangangi; Patrick Amoth; Kadondi Kasera; Wangari Ng'ang'a; Charles Rombo; Christine Yegon; Khamisi Kithi; Elizabeth Odhiambo; Thomas Rotich; Irene Orgut; Sammy Kihara; Christian Bottomley ORCID logo; Eunice W Kagucia ORCID logo; Katherine E Gallagher ORCID logo; Anthony Etyang; Shirine Voller ORCID logo; Teresa Lambe ORCID logo; Daniel Wright ORCID logo; Edwine Barasa; Benjamin Tsofa; Philip Bejon; Lynette I Ochola-Oyier; Ambrose Agweyu ORCID logo; J Anthony G Scott ORCID logo; George M Warimwe ORCID logo; (2021) Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya. Nature communications, 12 (1). 3966-. ISSN 2041-1723 DOI: 10.1038/s41467-021-24062-3
Copy

Observed SARS-CoV-2 infections and deaths are low in tropical Africa raising questions about the extent of transmission. We measured SARS-CoV-2 IgG by ELISA in 9,922 blood donors across Kenya and adjusted for sampling bias and test performance. By 1st September 2020, 577 COVID-19 deaths were observed nationwide and seroprevalence was 9.1% (95%CI 7.6-10.8%). Seroprevalence in Nairobi was 22.7% (18.0-27.7%). Although most people remained susceptible, SARS-CoV-2 had spread widely in Kenya with apparently low associated mortality.


picture_as_pdf
Adetifa_etal_2021_Temporal-trends-of-sars-cov.pdf
subject
Published Version
Available under Creative Commons: 3.0

View Download

Atom BibTeX OpenURL ContextObject in Span Multiline CSV OpenURL ContextObject Dublin Core Dublin Core MPEG-21 DIDL EndNote HTML Citation JSON MARC (ASCII) MARC (ISO 2709) METS MODS RDF+N3 RDF+N-Triples RDF+XML RIOXX2 XML Reference Manager Refer Simple Metadata ASCII Citation EP3 XML
Export

Downloads