Table 1.
Assay characteristics.
Fig 1.
A. Seroprevalence by month over the first COVID-19 wave in Canada by individual assays. Each line represents seroprevalence rates (summarized in table below) monthly between April and September 2020 (during the first COVID-19 Wave) based thresholds for each assay. Abbott Architect SARS-Cov-2 IgG assay (Abbott-NP) and three in-house IgG ELISA assays recognizing distinct recombinant viral antigens: full length spike glycoprotein (Spike), spike glycoprotein receptor binding domain (RBD), and nucleocapsid (NP). B. Seroprevalence by month over the first COVID-19 wave in Canada by various composite reference standards (results from four anti-SARS-CoV-2 immunoassays). Each line represents seroprevalence rates based on predefined definitions. CRS based on a combination of reactive samples using Abbott-NP, Spike, RBD and NP. Positivity based on “any two or more” was determined by a reactive sample from two or more assays. Since we are not comparing CRS, we did not include 95% CI for each data point (all overlapping).
Fig 2.
Seroprevalence estimates by different BLCM (informative, weakly informative and non-informative priors).
Each line represents seroprevalence rates (summarized in table below) derived from posterior means of three BLCMs (comparing informative, weakly informative and non-informative priors) bi-monthly between April and September 2020 (during the first COVID-19 Wave). Error bars represent 95% Credible Intervals.
Table 2.
Diagnostic phenotypes of anti-SARS-CoV-2 immunoassay results from 8999 samples tested.
Table 3.
Seroprevalence and assay characteristics overall and bi-monthly based on the Bayesian latent class analysis with informative priors.
Fig 3.
Summary comparison of seroprevalence rates by analytical methods.
Each line represents seroprevalence rates (summarized in table below) derived from four analytical methods bi-monthly between April and September 2020 (during the first COVID-19 Wave). > = 2 proteins (positivity was determined by a reactive sample from two or more assays), BLCA-Bayesian latent class analysis with informative priors, results are posterior means and error bars are 95% CrI and Abbott-NP is a single commercial assay.