Estimation of SARS-CoV-2 antibody prevalence through integration of serology and incidence data
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Abstract
Serology tests for SARS-CoV-2 provide a paradigm for estimating the number of individuals who have had infection in the past (including cases that are not detected by routine testing, which has varied over the course of the pandemic and between jurisdictions). Classical statistical approaches to such estimation do not incorporate case counts over time, and may be inaccurate due to uncertainty about the sensitivity and specificity of the serology test. In this work, we provide a joint Bayesian model for case counts and serological data, integrating uncertainty through priors on the sensitivity and specificity. We also model the Phases of the pandemic with exponential growth and decay. This model improves upon maximum likelihood estimates by conditioning on more data, and by taking into account the epidemiological trajectory. We apply our model to the greater Vancouver area, British Columbia, Canada with data acquired during Phase 1 of the pandemic.
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SciScore for 10.1101/2021.03.27.21254471: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources Immunoassays are used to determine how many people have been infected with COVID-19, by testing if an individual has SARS-CoV-2 antibodies (we use data from Skowronski et al. 2020, which tests for S1 spike, nucleocapsid and S1 receptor binding domain by combining the Vitros XT 7600 analyzer, the ARCHITECT i2000SR analyzer from Abbot Laboratories and the ADVIA Centaur XPT system). SARS-CoV-2suggested: NoneResults from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage …SciScore for 10.1101/2021.03.27.21254471: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources Immunoassays are used to determine how many people have been infected with COVID-19, by testing if an individual has SARS-CoV-2 antibodies (we use data from Skowronski et al. 2020, which tests for S1 spike, nucleocapsid and S1 receptor binding domain by combining the Vitros XT 7600 analyzer, the ARCHITECT i2000SR analyzer from Abbot Laboratories and the ADVIA Centaur XPT system). SARS-CoV-2suggested: NoneResults from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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