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Modeling serological testing to inform relaxation of social distancing for COVID-19 control

Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission ris...

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Autores principales: Kraay, Alicia N. M., Nelson, Kristin N., Zhao, Conan Y., Demory, David, Weitz, Joshua S., Lopman, Benjamin A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642547/
https://www.ncbi.nlm.nih.gov/pubmed/34862373
http://dx.doi.org/10.1038/s41467-021-26774-y
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author Kraay, Alicia N. M.
Nelson, Kristin N.
Zhao, Conan Y.
Demory, David
Weitz, Joshua S.
Lopman, Benjamin A.
author_facet Kraay, Alicia N. M.
Nelson, Kristin N.
Zhao, Conan Y.
Demory, David
Weitz, Joshua S.
Lopman, Benjamin A.
author_sort Kraay, Alicia N. M.
collection PubMed
description Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants.
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spelling pubmed-86425472021-12-15 Modeling serological testing to inform relaxation of social distancing for COVID-19 control Kraay, Alicia N. M. Nelson, Kristin N. Zhao, Conan Y. Demory, David Weitz, Joshua S. Lopman, Benjamin A. Nat Commun Article Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants. Nature Publishing Group UK 2021-12-03 /pmc/articles/PMC8642547/ /pubmed/34862373 http://dx.doi.org/10.1038/s41467-021-26774-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kraay, Alicia N. M.
Nelson, Kristin N.
Zhao, Conan Y.
Demory, David
Weitz, Joshua S.
Lopman, Benjamin A.
Modeling serological testing to inform relaxation of social distancing for COVID-19 control
title Modeling serological testing to inform relaxation of social distancing for COVID-19 control
title_full Modeling serological testing to inform relaxation of social distancing for COVID-19 control
title_fullStr Modeling serological testing to inform relaxation of social distancing for COVID-19 control
title_full_unstemmed Modeling serological testing to inform relaxation of social distancing for COVID-19 control
title_short Modeling serological testing to inform relaxation of social distancing for COVID-19 control
title_sort modeling serological testing to inform relaxation of social distancing for covid-19 control
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642547/
https://www.ncbi.nlm.nih.gov/pubmed/34862373
http://dx.doi.org/10.1038/s41467-021-26774-y
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