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. PLOS ONE. 2021 Sep 23. doi: https://doi.org/10.1371/journal.pone.0257743
The results and/or conclusions contained in the research do not necessarily reflect the views of all CITF members.
Despite the many assays available to test for SARS-CoV-2 antibodies, a gold standard has not yet been established. In an article now published in PLOS ONE, CITF Testing Working Group members Dr. Anne-Claude Gingras from the University of Toronto, and Dr. Steven Drews from Canadian Blood Services, evaluate multiple testing platforms and the concordance between test results in this CITF-funded study. Percentage values in this published version differ slightly from the preprint.
– As results differ between assay types and analytic methods, the authors suggest using a statistical model that combines results from multiple assays when estimating seroprevalence.
– This exercise confirmed that seroprevalence was very low during the first pandemic wave in Canada (<1%) and increased gradually from April (0.7%) to September 2020 (0.9%).
The authors used residual blood samples collected from April to September 2020 as part of the Canadian Blood Services serosurvey. SARS-CoV-2 antibodies were assessed by four unique assays (see table below). Seroprevalence was estimated using two different statistical methods, one that classifies an individual as ‘positive’ or ‘negative’ and another that combines data from multiple assays. The Abbott tests used at Canadian Blood Services were provided by the CITF.
Results were found to vary considerably between assay platforms. Reasons for this variability include differences in individual test sensitivities and specificitiesSensitivity is a measure of a test’s capacity to correctly diagnose a positive result and specificity describes the test’s capacity to correctly identify negative samples.. The in-house assays had higher sensitivity (78.8-93.51%) than the Abbott assay (58.5%) in detecting positive samples. An additional consideration here is that as SARS-CoV-2 antibodies wane over time, the ability of the assays to detect them also diminishes.
The authors recommend using a statistical model that combines results from multiple assays when estimating seroprevalence to improve accuracy, particularly in low prevalence scenarios.
|Assay name||Viral antigen (IgG)||Manufacturer||Assay platform|
|Abbott Architect SARS-CoV-2 IgG assay||Nucleocapsid||Abbott, Chicago IL||Commercial|
|Spike||Full length spike glycoprotein||Dr. Anne-Claude Gingras lab, Lunenfeld-Tanenbaum Research Institute, Toronto,||In-house|
|RBD||Spike glycoprotein receptor binding domain||Dr. Anne-Claude Gingras lab, Lunenfeld-Tanenbaum Research Institute, Toronto Dr.||In-house|
|NP||Nucleocapsid||Anne-Claude Gingras lab, Lunenfeld-Tanenbaum Research Institute, Toronto||In-house|