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Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination
Tools that can be used to estimate antibody waning following COVID-19 vaccinations can facilitate an understanding of the current immune status of the population. In this study, a two-compartment-based mathematical model is formulated to describe the dynamics of the anti-SARS-CoV-2 antibody in healt...
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/PMC9988198/ https://www.ncbi.nlm.nih.gov/pubmed/36878929 http://dx.doi.org/10.1038/s41541-023-00626-w |
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author | Uwamino, Yoshifumi Nagashima, Kengo Yoshifuji, Ayumi Suga, Shigeru Nagao, Mizuho Fujisawa, Takao Ryuzaki, Munekazu Takemoto, Yoshiaki Namkoong, Ho Wakui, Masatoshi Matsushita, Hiromichi Hasegawa, Naoki Sato, Yasunori Murata, Mitsuru |
author_facet | Uwamino, Yoshifumi Nagashima, Kengo Yoshifuji, Ayumi Suga, Shigeru Nagao, Mizuho Fujisawa, Takao Ryuzaki, Munekazu Takemoto, Yoshiaki Namkoong, Ho Wakui, Masatoshi Matsushita, Hiromichi Hasegawa, Naoki Sato, Yasunori Murata, Mitsuru |
author_sort | Uwamino, Yoshifumi |
collection | PubMed |
description | Tools that can be used to estimate antibody waning following COVID-19 vaccinations can facilitate an understanding of the current immune status of the population. In this study, a two-compartment-based mathematical model is formulated to describe the dynamics of the anti-SARS-CoV-2 antibody in healthy adults using serially measured waning antibody concentration data obtained in a prospective cohort study of 673 healthcare providers vaccinated with two doses of BNT162b2 vaccine. The datasets of 165 healthcare providers and 292 elderly patients with or without hemodialysis were used for external validation. Internal validation of the model demonstrated 97.0% accuracy, and external validation of the datasets of healthcare workers, hemodialysis patients, and nondialysis patients demonstrated 98.2%, 83.3%, and 83.8% accuracy, respectively. The internal and external validations demonstrated that this model also fits the data of various populations with or without underlying illnesses. Furthermore, using this model, we developed a smart device application that can rapidly calculate the timing of negative seroconversion. |
format | Online Article Text |
id | pubmed-9988198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99881982023-03-07 Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination Uwamino, Yoshifumi Nagashima, Kengo Yoshifuji, Ayumi Suga, Shigeru Nagao, Mizuho Fujisawa, Takao Ryuzaki, Munekazu Takemoto, Yoshiaki Namkoong, Ho Wakui, Masatoshi Matsushita, Hiromichi Hasegawa, Naoki Sato, Yasunori Murata, Mitsuru NPJ Vaccines Article Tools that can be used to estimate antibody waning following COVID-19 vaccinations can facilitate an understanding of the current immune status of the population. In this study, a two-compartment-based mathematical model is formulated to describe the dynamics of the anti-SARS-CoV-2 antibody in healthy adults using serially measured waning antibody concentration data obtained in a prospective cohort study of 673 healthcare providers vaccinated with two doses of BNT162b2 vaccine. The datasets of 165 healthcare providers and 292 elderly patients with or without hemodialysis were used for external validation. Internal validation of the model demonstrated 97.0% accuracy, and external validation of the datasets of healthcare workers, hemodialysis patients, and nondialysis patients demonstrated 98.2%, 83.3%, and 83.8% accuracy, respectively. The internal and external validations demonstrated that this model also fits the data of various populations with or without underlying illnesses. Furthermore, using this model, we developed a smart device application that can rapidly calculate the timing of negative seroconversion. Nature Publishing Group UK 2023-03-06 /pmc/articles/PMC9988198/ /pubmed/36878929 http://dx.doi.org/10.1038/s41541-023-00626-w 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 Uwamino, Yoshifumi Nagashima, Kengo Yoshifuji, Ayumi Suga, Shigeru Nagao, Mizuho Fujisawa, Takao Ryuzaki, Munekazu Takemoto, Yoshiaki Namkoong, Ho Wakui, Masatoshi Matsushita, Hiromichi Hasegawa, Naoki Sato, Yasunori Murata, Mitsuru Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination |
title | Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination |
title_full | Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination |
title_fullStr | Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination |
title_full_unstemmed | Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination |
title_short | Estimating immunity with mathematical models for SARS-CoV-2 after COVID-19 vaccination |
title_sort | estimating immunity with mathematical models for sars-cov-2 after covid-19 vaccination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988198/ https://www.ncbi.nlm.nih.gov/pubmed/36878929 http://dx.doi.org/10.1038/s41541-023-00626-w |
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