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Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach
With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta,...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356855/ https://www.ncbi.nlm.nih.gov/pubmed/37468463 http://dx.doi.org/10.1038/s41467-023-39736-3 |
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author | Hogan, Alexandra B. Doohan, Patrick Wu, Sean L. Mesa, Daniela Olivera Toor, Jaspreet Watson, Oliver J. Winskill, Peter Charles, Giovanni Barnsley, Gregory Riley, Eleanor M. Khoury, David S. Ferguson, Neil M. Ghani, Azra C. |
author_facet | Hogan, Alexandra B. Doohan, Patrick Wu, Sean L. Mesa, Daniela Olivera Toor, Jaspreet Watson, Oliver J. Winskill, Peter Charles, Giovanni Barnsley, Gregory Riley, Eleanor M. Khoury, David S. Ferguson, Neil M. Ghani, Azra C. |
author_sort | Hogan, Alexandra B. |
collection | PubMed |
description | With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the ancestral vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness. |
format | Online Article Text |
id | pubmed-10356855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103568552023-07-21 Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach Hogan, Alexandra B. Doohan, Patrick Wu, Sean L. Mesa, Daniela Olivera Toor, Jaspreet Watson, Oliver J. Winskill, Peter Charles, Giovanni Barnsley, Gregory Riley, Eleanor M. Khoury, David S. Ferguson, Neil M. Ghani, Azra C. Nat Commun Article With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the ancestral vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness. Nature Publishing Group UK 2023-07-19 /pmc/articles/PMC10356855/ /pubmed/37468463 http://dx.doi.org/10.1038/s41467-023-39736-3 Text en © The Author(s) 2023 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 Hogan, Alexandra B. Doohan, Patrick Wu, Sean L. Mesa, Daniela Olivera Toor, Jaspreet Watson, Oliver J. Winskill, Peter Charles, Giovanni Barnsley, Gregory Riley, Eleanor M. Khoury, David S. Ferguson, Neil M. Ghani, Azra C. Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach |
title | Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach |
title_full | Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach |
title_fullStr | Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach |
title_full_unstemmed | Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach |
title_short | Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach |
title_sort | estimating long-term vaccine effectiveness against sars-cov-2 variants: a model-based approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356855/ https://www.ncbi.nlm.nih.gov/pubmed/37468463 http://dx.doi.org/10.1038/s41467-023-39736-3 |
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