Substantial underestimation of SARS-CoV-2 infection in the United States
Fecha
2020Autor
Wu, Sean L.
Mertens, Andrew N.
Crider, Yoshika S.
Nguyen, Anna
Pokpongkiat, Nolan N.
Djajadi, Stephanie
Seth, Anmol
Hsiang, Michelle S.
Colford Jr., John M.
Reingold, Art
Arnold, Benjamin F.
Hubbard, Alan
Benjamin-Chung, Jade
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Resumen
Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic
response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the
pandemic because testing has been primarily restricted to individuals with moderate to
severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic
bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We
estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs.
0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty,
the number of infections during this period was 3 to 20 times higher than the number of
confirmed cases. 86% (simulation interval: 64–99%) of this difference is due to incomplete
testing, while 14% (0.3–36%) is due to imperfect test accuracy. The approach can readily be
applied in future studies in other locations or at finer spatial scale to correct for biased testing
and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19
burden.
Palabras clave
SARS-CoV-2; SARS-CoV-2 Infection; United StatesEnlace al recurso
https://doi.org/10.1038/s41467-020-18272-4Colecciones
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