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Estimating the undetected emergence of COVID-19 in the US

As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and local authorities were left to make rapid decisions ba...

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Autores principales: Javan, Emily M., Fox, Spencer J., Meyers, Lauren Ancel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079060/
https://www.ncbi.nlm.nih.gov/pubmed/37023065
http://dx.doi.org/10.1371/journal.pone.0284025
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author Javan, Emily M.
Fox, Spencer J.
Meyers, Lauren Ancel
author_facet Javan, Emily M.
Fox, Spencer J.
Meyers, Lauren Ancel
author_sort Javan, Emily M.
collection PubMed
description As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and local authorities were left to make rapid decisions based on limited case data and scientific information to protect their communities. To support local decision making in early 2020, we developed a model for estimating the probability of an undetected COVID-19 epidemic (epidemic risk) in each US county based on the epidemiological characteristics of the virus and the number of confirmed and suspected cases. As a retrospective analysis we included county-specific reproduction numbers and found that counties with only a single reported case by March 16, 2020 had a mean epidemic risk of 71% (95% CI: 52–83%), implying COVID-19 was already spreading widely by the first detected case. By that date, 15% of US counties covering 63% of the population had reported at least one case and had epidemic risk greater than 50%. We find that a 10% increase in model estimated epidemic risk for March 16 yields a 0.53 (95% CI: 0.49–0.58) increase in the log odds that the county reported at least two additional cases in the following week. The original epidemic risk estimates made on March 16, 2020 that assumed all counties had an effective reproduction number of 3.0 are highly correlated with our retrospective estimates (r = 0.99; p<0.001) but are less predictive of subsequent case increases (AIC difference of 93.3 and 100% weight in favor of the retrospective risk estimates). Given the low rates of testing and reporting early in the pandemic, taking action upon the detection of just one or a few cases may be prudent.
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spelling pubmed-100790602023-04-07 Estimating the undetected emergence of COVID-19 in the US Javan, Emily M. Fox, Spencer J. Meyers, Lauren Ancel PLoS One Research Article As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and local authorities were left to make rapid decisions based on limited case data and scientific information to protect their communities. To support local decision making in early 2020, we developed a model for estimating the probability of an undetected COVID-19 epidemic (epidemic risk) in each US county based on the epidemiological characteristics of the virus and the number of confirmed and suspected cases. As a retrospective analysis we included county-specific reproduction numbers and found that counties with only a single reported case by March 16, 2020 had a mean epidemic risk of 71% (95% CI: 52–83%), implying COVID-19 was already spreading widely by the first detected case. By that date, 15% of US counties covering 63% of the population had reported at least one case and had epidemic risk greater than 50%. We find that a 10% increase in model estimated epidemic risk for March 16 yields a 0.53 (95% CI: 0.49–0.58) increase in the log odds that the county reported at least two additional cases in the following week. The original epidemic risk estimates made on March 16, 2020 that assumed all counties had an effective reproduction number of 3.0 are highly correlated with our retrospective estimates (r = 0.99; p<0.001) but are less predictive of subsequent case increases (AIC difference of 93.3 and 100% weight in favor of the retrospective risk estimates). Given the low rates of testing and reporting early in the pandemic, taking action upon the detection of just one or a few cases may be prudent. Public Library of Science 2023-04-06 /pmc/articles/PMC10079060/ /pubmed/37023065 http://dx.doi.org/10.1371/journal.pone.0284025 Text en © 2023 Javan et al 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
Javan, Emily M.
Fox, Spencer J.
Meyers, Lauren Ancel
Estimating the undetected emergence of COVID-19 in the US
title Estimating the undetected emergence of COVID-19 in the US
title_full Estimating the undetected emergence of COVID-19 in the US
title_fullStr Estimating the undetected emergence of COVID-19 in the US
title_full_unstemmed Estimating the undetected emergence of COVID-19 in the US
title_short Estimating the undetected emergence of COVID-19 in the US
title_sort estimating the undetected emergence of covid-19 in the us
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079060/
https://www.ncbi.nlm.nih.gov/pubmed/37023065
http://dx.doi.org/10.1371/journal.pone.0284025
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