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A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal
The governors of New Jersey, New York, California, Connecticut, Delaware and Oregon announced early in the week of February 7 that select mask mandates in their states would end in two to six weeks. These states together account for 77.9 million Americans, or ~23.5% of the U.S. population, and there...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202658/ https://www.ncbi.nlm.nih.gov/pubmed/35721376 http://dx.doi.org/10.14218/ERHM.2022.00025 |
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author | Chen, Cynthia Shen, Shiqian |
author_facet | Chen, Cynthia Shen, Shiqian |
author_sort | Chen, Cynthia |
collection | PubMed |
description | The governors of New Jersey, New York, California, Connecticut, Delaware and Oregon announced early in the week of February 7 that select mask mandates in their states would end in two to six weeks. These states together account for 77.9 million Americans, or ~23.5% of the U.S. population, and therefore these changes in policy could have a significant impact on the U.S. economy, as well as education and healthcare systems in each state. As counts of COVID-19 cases, hospitalizations and deaths decrease, mask mandates should be reassessed. We propose that a data-driven, dynamic and flexible approach may help lift mask mandates safely and facilitate a smooth transition to post-pandemic normalcy. |
format | Online Article Text |
id | pubmed-9202658 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-92026582022-06-16 A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal Chen, Cynthia Shen, Shiqian Explor Res Hypothesis Med Article The governors of New Jersey, New York, California, Connecticut, Delaware and Oregon announced early in the week of February 7 that select mask mandates in their states would end in two to six weeks. These states together account for 77.9 million Americans, or ~23.5% of the U.S. population, and therefore these changes in policy could have a significant impact on the U.S. economy, as well as education and healthcare systems in each state. As counts of COVID-19 cases, hospitalizations and deaths decrease, mask mandates should be reassessed. We propose that a data-driven, dynamic and flexible approach may help lift mask mandates safely and facilitate a smooth transition to post-pandemic normalcy. 2022-06 2022-02-25 /pmc/articles/PMC9202658/ /pubmed/35721376 http://dx.doi.org/10.14218/ERHM.2022.00025 Text en https://creativecommons.org/licenses/by-nc/4.0/This article has been published under the terms of Creative Commons Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/) , which permits noncommercial unrestricted use, distribution, and reproduction in any medium, provided that the following statement is provided. |
spellingShingle | Article Chen, Cynthia Shen, Shiqian A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal |
title | A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal |
title_full | A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal |
title_fullStr | A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal |
title_full_unstemmed | A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal |
title_short | A Data-driven, Dynamic and Flexible Approach to Safely Lifting Mask Mandate: A Proposal |
title_sort | data-driven, dynamic and flexible approach to safely lifting mask mandate: a proposal |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202658/ https://www.ncbi.nlm.nih.gov/pubmed/35721376 http://dx.doi.org/10.14218/ERHM.2022.00025 |
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