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A framework for monitoring population immunity to SARS-CoV-2

In the effort to control SARS-CoV-2 transmission, public health agencies in the United States and globally are aiming to increase population immunity. Immunity through vaccination and acquired following recovery from natural infection are the two means to build up population immunity, with vaccinati...

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Autores principales: Lopman, Benjamin A., Shioda, Kayoko, Nguyen, Quan, Beckett, Stephen J., Siegler, Aaron J., Sullivan, Patrick S., Weitz, Joshua S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379082/
https://www.ncbi.nlm.nih.gov/pubmed/34425208
http://dx.doi.org/10.1016/j.annepidem.2021.08.013
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author Lopman, Benjamin A.
Shioda, Kayoko
Nguyen, Quan
Beckett, Stephen J.
Siegler, Aaron J.
Sullivan, Patrick S.
Weitz, Joshua S.
author_facet Lopman, Benjamin A.
Shioda, Kayoko
Nguyen, Quan
Beckett, Stephen J.
Siegler, Aaron J.
Sullivan, Patrick S.
Weitz, Joshua S.
author_sort Lopman, Benjamin A.
collection PubMed
description In the effort to control SARS-CoV-2 transmission, public health agencies in the United States and globally are aiming to increase population immunity. Immunity through vaccination and acquired following recovery from natural infection are the two means to build up population immunity, with vaccination being the safe pathway. However, measuring the contribution to population immunity from vaccination or natural infection is non-trivial. Historical COVID-19 case counts and vaccine coverage are necessary information but are not sufficient to approximate population immunity. Here, we consider the nuances of measuring each and propose an analytical framework for integrating the necessary data on cumulative vaccinations and natural infections at the state and national level. To guide vaccine roll-out and other aspects of control over the coming months, we recommend analytics that combine vaccine coverage with local (e.g. county-level) history of case reports and adjustment for waning antibodies to establish local estimates of population immunity. To do so, the strategic use of minimally-biased serology surveys integrated with vaccine administration data can improve estimates of the aggregate level of immunity to guide data-driven decisions to re-open safely and prioritize vaccination efforts.
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spelling pubmed-83790822021-08-23 A framework for monitoring population immunity to SARS-CoV-2 Lopman, Benjamin A. Shioda, Kayoko Nguyen, Quan Beckett, Stephen J. Siegler, Aaron J. Sullivan, Patrick S. Weitz, Joshua S. Ann Epidemiol Commentary In the effort to control SARS-CoV-2 transmission, public health agencies in the United States and globally are aiming to increase population immunity. Immunity through vaccination and acquired following recovery from natural infection are the two means to build up population immunity, with vaccination being the safe pathway. However, measuring the contribution to population immunity from vaccination or natural infection is non-trivial. Historical COVID-19 case counts and vaccine coverage are necessary information but are not sufficient to approximate population immunity. Here, we consider the nuances of measuring each and propose an analytical framework for integrating the necessary data on cumulative vaccinations and natural infections at the state and national level. To guide vaccine roll-out and other aspects of control over the coming months, we recommend analytics that combine vaccine coverage with local (e.g. county-level) history of case reports and adjustment for waning antibodies to establish local estimates of population immunity. To do so, the strategic use of minimally-biased serology surveys integrated with vaccine administration data can improve estimates of the aggregate level of immunity to guide data-driven decisions to re-open safely and prioritize vaccination efforts. Elsevier Inc. 2021-11 2021-08-21 /pmc/articles/PMC8379082/ /pubmed/34425208 http://dx.doi.org/10.1016/j.annepidem.2021.08.013 Text en © 2021 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Commentary
Lopman, Benjamin A.
Shioda, Kayoko
Nguyen, Quan
Beckett, Stephen J.
Siegler, Aaron J.
Sullivan, Patrick S.
Weitz, Joshua S.
A framework for monitoring population immunity to SARS-CoV-2
title A framework for monitoring population immunity to SARS-CoV-2
title_full A framework for monitoring population immunity to SARS-CoV-2
title_fullStr A framework for monitoring population immunity to SARS-CoV-2
title_full_unstemmed A framework for monitoring population immunity to SARS-CoV-2
title_short A framework for monitoring population immunity to SARS-CoV-2
title_sort framework for monitoring population immunity to sars-cov-2
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379082/
https://www.ncbi.nlm.nih.gov/pubmed/34425208
http://dx.doi.org/10.1016/j.annepidem.2021.08.013
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