Saeed S, O’Brien SF, Abe K, Yi O, Rathod B, Wang J, Fazel-Zarandi M, Tuite A, Fisman D, Wood H, Colwill K, Gingras A-C, Drews S. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence: Navigating the absence of a gold standard. medRxiv. 2021 May 12. doi: 10.1101/2021.05.11.21256992.
The results and/or conclusions contained in the research do not necessarily reflect the views of all CITF members.
A recent preprint, not yet peer reviewed, by CITF Testing Working Group members Dr. Anne-Claude Gingras from University of Toronto, and Dr. Steven Drews from Canadian Blood Services, compared multiple assays and concluded ‘Made-in-Canada’ ones performed well.
Blood samples were collected through Canadian Blood Services between April and September 2020. A total of 8999 donors across Canada were included. SARS-CoV-2 antibodies were assessed by four assays: a common commercial assay called Abbott Architect SARS-CoV-2 IgG which targets the nucleocapsid (N) protein and three in-house IgG ELISA assays from Dr. Gingras’ lab that recognize different SARS-CoV-2 proteins including the spike (S), receptor binding domain (RBD) and the N. Seroprevalence was estimated using two different statistical methods, one of which classifies an individual as positive or negative, while the other combines data from multiple assays.
Overall, the in-house ELISA assays had higher sensitivity (71.8-89.1%) than the Abbott assay (51.6% sensitivity) in detecting positive samples. Among the in-house ELISA assays, specificity was highest for the RBD protein and lowest for the N protein. As SARS-CoV-2 antibodies waned, the ability for the assays to detect them also diminished.
Given a low prevalence setting and waning SARS-CoV-2 antibody levels over time, authors recommended a statistical model that combines results from multiple assays should be used to estimate seroprevalence. This novel approach may be applicable to other low prevalence microbes that can cause disease.