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Activity Number:
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71
- COVID-19 and Survey Research Methods
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Type:
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Contributed
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Date/Time:
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Sunday, August 7, 2022 : 4:00 PM to 5:50 PM
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Sponsor:
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Survey Research Methods Section
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Abstract #322794
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Title:
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Estimating SARS-CoV-2 Seroprevalence
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Author(s):
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Samuel P Rosin* and Bonnie Shook-Sa and Stephen R Cole and Michael Hudgens
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Companies:
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University of North Carolina at Chapel Hill and University of North Carolina - Chapel Hill and UNC Chapel Hill and University of North Carolina at Chapel Hill
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Keywords:
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Covid-19;
Diagnostic tests;
Estimating equations;
Seroepidemiologic studies;
Standardization
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Abstract:
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Governments and public health authorities use seroprevalence studies to guide their responses to the COVID-19 pandemic. These seroprevalence surveys estimate the proportion of persons within a given population who have detectable antibodies to SARS-CoV-2. However, serologic assays are prone to misclassification error due to false positives and negatives, and non-probability sampling methods may induce selection bias. We consider nonparametric and parametric seroprevalence estimators that address both challenges by leveraging validation data and assuming equal probabilities of sample inclusion within covariate-defined strata. Both estimators are shown to be consistent and asymptotically normal, and consistent variance estimators are derived. Simulation studies are presented comparing the finite sample performance of the estimators over a range of assay characteristics and sampling scenarios. The methods are used to estimate SARS-CoV-2 seroprevalence in Belgium and North Carolina.
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Authors who are presenting talks have a * after their name.
