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Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels
The US Centers for Disease Control and Prevention (CDC) defines a county metric of coronavirus disease 2019 (COVID-19) community levels to inform public health measures. We find that the COVID-19 community levels vary frequently over time, which may not be optimal for decision making. Alternative me...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10110267/ https://www.ncbi.nlm.nih.gov/pubmed/36433715 http://dx.doi.org/10.1093/cid/ciac922 |
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author | Mokhtar, Sina Parpia, Alyssa S Lo, Nathan C Ndeffo-Mbah, Martial L |
author_facet | Mokhtar, Sina Parpia, Alyssa S Lo, Nathan C Ndeffo-Mbah, Martial L |
author_sort | Mokhtar, Sina |
collection | PubMed |
description | The US Centers for Disease Control and Prevention (CDC) defines a county metric of coronavirus disease 2019 (COVID-19) community levels to inform public health measures. We find that the COVID-19 community levels vary frequently over time, which may not be optimal for decision making. Alternative metric formulations that do not compromise predictive ability are shown to reduce variability. |
format | Online Article Text |
id | pubmed-10110267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101102672023-04-18 Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels Mokhtar, Sina Parpia, Alyssa S Lo, Nathan C Ndeffo-Mbah, Martial L Clin Infect Dis Brief Report The US Centers for Disease Control and Prevention (CDC) defines a county metric of coronavirus disease 2019 (COVID-19) community levels to inform public health measures. We find that the COVID-19 community levels vary frequently over time, which may not be optimal for decision making. Alternative metric formulations that do not compromise predictive ability are shown to reduce variability. Oxford University Press 2022-11-26 /pmc/articles/PMC10110267/ /pubmed/36433715 http://dx.doi.org/10.1093/cid/ciac922 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Brief Report Mokhtar, Sina Parpia, Alyssa S Lo, Nathan C Ndeffo-Mbah, Martial L Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels |
title | Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels |
title_full | Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels |
title_fullStr | Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels |
title_full_unstemmed | Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels |
title_short | Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels |
title_sort | evaluation of the us definitions for coronavirus disease 2019 community risk levels |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10110267/ https://www.ncbi.nlm.nih.gov/pubmed/36433715 http://dx.doi.org/10.1093/cid/ciac922 |
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