Comparative performance of the InBios SCoV-2 DetectTM IgG ELISA and the in-house KWTRP ELISA in detecting SARS-CoV-2 spike IgG antibodies in Kenyan populations

Author:

Kutima BernadetteORCID,Kagucia Eunice Wageci,Mwai Kennedy,Kimani MakobuORCID,Sigilai Antipa,Mugo Daisy,Karanja HenryORCID,Gitonga John NORCID,Karani Angela,Akech Donald,Toroitich Monica,Karia Boniface,Tuju James,Ziraba Abdhalah K.,Bigogo Godfrey,Ochieng Caroline,Onyango Clayton,Lidechi Shirley,Munywoki Patrick K.ORCID,Uyoga SophieORCID,Adetifa Ifedayo M. O.,Oyier Lynette I Ochola,Bejon PhilipORCID,Scott J Anthony GORCID,Agweyu AmbroseORCID,Warimwe George M.ORCID,Nyagwange JamesORCID,

Abstract

Background The InBios SCoV-2 DetectTM IgG ELISA (InBios) and the in-house KWTRP ELISA (KWTRP) have both been used in the estimation of SARS-CoV-2 seroprevalence in Kenya. Whereas the latter has been validated extensively using local samples, the former has not. Such validation is important for informing the comparability of data across the sites and populations where seroprevalence has been reported. Methods We compared the assays directly using pre-pandemic serum/plasma collected in 2018 from 454 blood donors and 173 malaria cross-sectional survey participants, designated gold standard negatives. As gold standard SARS-CoV-2 positive samples: we assayed serum/plasma from 159 SARS-CoV-2 PCR-positive patients and 166 vaccination-confirmed participants. Results The overall agreement on correctly classified samples was >0.87 for both assays. The overall specificity was 0.89 (95% CI, 0.87–0.91) for InBios and 0.99 (95% CI, 0.97–0.99) for KWTRP among the gold standard negative samples while the overall sensitivity was 0.97 (95% CI, 0.94–0.98) and 0.93 (95% CI, 0.90– 0.95) for InBios and KWTRP ELISAs respectively, among the gold standard positive samples. Conclusions Overall, both assays showed sufficient sensitivity and specificity to estimate SARS-CoV-2 antibodies in different populations in Kenya.

Funder

Bill and Melinda Gates Foundation

Wellcome Trust

Publisher

F1000 Research Ltd

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