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Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States

Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses and vaccination coverage needed to address the ongoing spread of COVID-19 in each United States (U.S.) state. However, reliable, timely data based on representative popula...

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Autores principales: Chiu, Weihsueh A., Ndeffo-Mbah, Martial L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448371/
https://www.ncbi.nlm.nih.gov/pubmed/34491990
http://dx.doi.org/10.1371/journal.pcbi.1009374
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author Chiu, Weihsueh A.
Ndeffo-Mbah, Martial L.
author_facet Chiu, Weihsueh A.
Ndeffo-Mbah, Martial L.
author_sort Chiu, Weihsueh A.
collection PubMed
description Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses and vaccination coverage needed to address the ongoing spread of COVID-19 in each United States (U.S.) state. However, reliable, timely data based on representative population sampling are unavailable, and reported case and test positivity rates are highly biased. A simple data-driven Bayesian semi-empirical modeling framework was developed and used to evaluate state-level prevalence and seroprevalence of COVID-19 using daily reported cases and test positivity ratios. The model was calibrated to and validated using published state-wide seroprevalence data, and further compared against two independent data-driven mathematical models. The prevalence of undiagnosed COVID-19 infections is found to be well-approximated by a geometrically weighted average of the positivity rate and the reported case rate. Our model accurately fits state-level seroprevalence data from across the U.S. Prevalence estimates of our semi-empirical model compare favorably to those from two data-driven epidemiological models. As of December 31, 2020, we estimate nation-wide a prevalence of 1.4% [Credible Interval (CrI): 1.0%-1.9%] and a seroprevalence of 13.2% [CrI: 12.3%-14.2%], with state-level prevalence ranging from 0.2% [CrI: 0.1%-0.3%] in Hawaii to 2.8% [CrI: 1.8%-4.1%] in Tennessee, and seroprevalence from 1.5% [CrI: 1.2%-2.0%] in Vermont to 23% [CrI: 20%-28%] in New York. Cumulatively, reported cases correspond to only one third of actual infections. The use of this simple and easy-to-communicate approach to estimating COVID-19 prevalence and seroprevalence will improve the ability to make public health decisions that effectively respond to the ongoing COVID-19 pandemic.
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spelling pubmed-84483712021-09-18 Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States Chiu, Weihsueh A. Ndeffo-Mbah, Martial L. PLoS Comput Biol Research Article Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses and vaccination coverage needed to address the ongoing spread of COVID-19 in each United States (U.S.) state. However, reliable, timely data based on representative population sampling are unavailable, and reported case and test positivity rates are highly biased. A simple data-driven Bayesian semi-empirical modeling framework was developed and used to evaluate state-level prevalence and seroprevalence of COVID-19 using daily reported cases and test positivity ratios. The model was calibrated to and validated using published state-wide seroprevalence data, and further compared against two independent data-driven mathematical models. The prevalence of undiagnosed COVID-19 infections is found to be well-approximated by a geometrically weighted average of the positivity rate and the reported case rate. Our model accurately fits state-level seroprevalence data from across the U.S. Prevalence estimates of our semi-empirical model compare favorably to those from two data-driven epidemiological models. As of December 31, 2020, we estimate nation-wide a prevalence of 1.4% [Credible Interval (CrI): 1.0%-1.9%] and a seroprevalence of 13.2% [CrI: 12.3%-14.2%], with state-level prevalence ranging from 0.2% [CrI: 0.1%-0.3%] in Hawaii to 2.8% [CrI: 1.8%-4.1%] in Tennessee, and seroprevalence from 1.5% [CrI: 1.2%-2.0%] in Vermont to 23% [CrI: 20%-28%] in New York. Cumulatively, reported cases correspond to only one third of actual infections. The use of this simple and easy-to-communicate approach to estimating COVID-19 prevalence and seroprevalence will improve the ability to make public health decisions that effectively respond to the ongoing COVID-19 pandemic. Public Library of Science 2021-09-07 /pmc/articles/PMC8448371/ /pubmed/34491990 http://dx.doi.org/10.1371/journal.pcbi.1009374 Text en © 2021 Chiu, Ndeffo-Mbah https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chiu, Weihsueh A.
Ndeffo-Mbah, Martial L.
Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
title Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
title_full Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
title_fullStr Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
title_full_unstemmed Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
title_short Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
title_sort using test positivity and reported case rates to estimate state-level covid-19 prevalence and seroprevalence in the united states
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448371/
https://www.ncbi.nlm.nih.gov/pubmed/34491990
http://dx.doi.org/10.1371/journal.pcbi.1009374
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