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Citation

García-Carreras, Bernardo; Hitchings, Matt D. T.; Johansson, Michael A.; Biggerstaff, Matthew; Slayton, Rachel B.; Healy, Jessica M.; Lessler, Justin; Quandelacy, Talia M.; Salje, Henrik; & Huang, Angkana T., et al. (2023). Accounting For Assay Performance When Estimating the Temporal Dynamics in SARS-CoV-2 Seroprevalence in the U.S. Nature Communications, 14(1), 2235. PMCID: PMC10115837

Abstract

Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection.

URL

http://dx.doi.org/10.1038/s41467-023-37944-5

Reference Type

Journal Article

Year Published

2023

Journal Title

Nature Communications

Author(s)

García-Carreras, Bernardo
Hitchings, Matt D. T.
Johansson, Michael A.
Biggerstaff, Matthew
Slayton, Rachel B.
Healy, Jessica M.
Lessler, Justin
Quandelacy, Talia M.
Salje, Henrik
Huang, Angkana T.
Cummings, Derek A. T.

Article Type

Regular

PMCID

PMC10115837

Continent/Country

United States of America

State

Nonspecific

ORCiD

Lessler - 0000-0002-9741-8109