Abstract
BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence studies bridge the gap left from case detection, to estimate the true burden of the COVID-19 pandemic. While multiple anti-SARS-CoV-2 immunoassays are available, no gold standard exists.MethodsThis serial cross-sectional study was conducted using plasma samples from 8999 healthy blood donors between April-September 2020. Each sample was tested by four assays: Abbott SARS-Cov-2 IgG assay, targeting nucleocapsid (Abbott-NP) and three in-house IgG ELISA assays (targeting spike glycoprotein, receptor binding domain, and nucleocapsid). Seroprevalence rates were compared using multiple composite reference standards and by a series of Bayesian Latent Class Models.ResultWe found 13 unique diagnostic phenotypes; only 32 samples (0.4%) were positive by all assays. None of the individual assays resulted in seroprevalence increasing monotonically over time. In contrast, by using the results from all assays, the Bayesian Latent Class Model with informative priors predicted seroprevalence increased from 0.7% (95% credible interval (95% CrI); 0.4, 1.0%) in April/May to 0.7% (95% CrI 0.5, 1.1%) in June/July to 0.9% (95% CrI 0.5, 1.3) in August/September. Assay characteristics varied over time. Overall Spike had the highest sensitivity (93.5% (95% CrI 88.7, 97.3%), while the sensitivity of the Abbott-NP assay waned from 77.3% (95% CrI 58.7, 92.5%) in April/May to 64.4% (95% CrI 45.6, 83.0) by August/September.DiscussionOur results confirmed very low seroprevalence after the first wave in Canada. Given the dynamic nature of this pandemic, Bayesian Latent Class Models can be used to correct for imperfect test characteristics and waning IgG antibody signals.
Highlights
Worldwide, more than 159 million people have been diagnosed with coronavirus disease 2019 (COVID-19), as of May 13, 2021 [1]
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence studies bridge the gap left from case detection, to estimate the true burden of the COVID-19 pandemic
Rates were lower and more stable by receptor binding domain (RBD) that started at 0.8% and increased to 1.6% by September
Summary
More than 159 million people have been diagnosed with coronavirus disease 2019 (COVID-19), as of May 13, 2021 [1] This is likely an underestimation of the true burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) given testing is primarily used to confirm suspected infection as opposed to broad surveillance. Determining the proportion of individuals with evidence of an immune response to SARS-CoV-2 can provide a more comprehensive assessment of prevalence to assist public health officials in making policy decisions. This prompted an urgent need for seroprevalence studies and accurate anti-SARSCoV-2 immunoassays to estimate the true burden of disease. While multiple anti-SARS-CoV-2 immunoassays are available, no gold standard exists.
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