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Vaccinating Children against COVID-19: Commentary and Mathematical Modeling

With the recent licensure of mRNA vaccines against COVID-19 in the 5- to 11-year-old age group, the public health impact of a childhood immunization campaign is of interest. Using a mathematical epidemiological model, we project that childhood vaccination carries minimal risk and yields modest publi...

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Detalles Bibliográficos
Autores principales: Hawkes, Michael T., Good, Michael F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764932/
https://www.ncbi.nlm.nih.gov/pubmed/35040706
http://dx.doi.org/10.1128/mbio.03789-21
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author Hawkes, Michael T.
Good, Michael F.
author_facet Hawkes, Michael T.
Good, Michael F.
author_sort Hawkes, Michael T.
collection PubMed
description With the recent licensure of mRNA vaccines against COVID-19 in the 5- to 11-year-old age group, the public health impact of a childhood immunization campaign is of interest. Using a mathematical epidemiological model, we project that childhood vaccination carries minimal risk and yields modest public health benefits. These include large relative reductions in child morbidity and mortality, although the absolute reduction is small because these events are rare. Furthermore, the model predicts “altruistic” absolute reductions in adult cases, hospitalizations, and mortality. However, vaccinating children to benefit adults should be considered from an ethical as well as a public health perspective. From a global health perspective, an additional ethical consideration is the justice of giving priority to children in high-income settings at low risk of severe disease while vaccines have not been made available to vulnerable adults in low-income settings.
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spelling pubmed-87649322022-01-24 Vaccinating Children against COVID-19: Commentary and Mathematical Modeling Hawkes, Michael T. Good, Michael F. mBio Research Article With the recent licensure of mRNA vaccines against COVID-19 in the 5- to 11-year-old age group, the public health impact of a childhood immunization campaign is of interest. Using a mathematical epidemiological model, we project that childhood vaccination carries minimal risk and yields modest public health benefits. These include large relative reductions in child morbidity and mortality, although the absolute reduction is small because these events are rare. Furthermore, the model predicts “altruistic” absolute reductions in adult cases, hospitalizations, and mortality. However, vaccinating children to benefit adults should be considered from an ethical as well as a public health perspective. From a global health perspective, an additional ethical consideration is the justice of giving priority to children in high-income settings at low risk of severe disease while vaccines have not been made available to vulnerable adults in low-income settings. American Society for Microbiology 2022-01-18 /pmc/articles/PMC8764932/ /pubmed/35040706 http://dx.doi.org/10.1128/mbio.03789-21 Text en Copyright © 2022 Hawkes and Good. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Hawkes, Michael T.
Good, Michael F.
Vaccinating Children against COVID-19: Commentary and Mathematical Modeling
title Vaccinating Children against COVID-19: Commentary and Mathematical Modeling
title_full Vaccinating Children against COVID-19: Commentary and Mathematical Modeling
title_fullStr Vaccinating Children against COVID-19: Commentary and Mathematical Modeling
title_full_unstemmed Vaccinating Children against COVID-19: Commentary and Mathematical Modeling
title_short Vaccinating Children against COVID-19: Commentary and Mathematical Modeling
title_sort vaccinating children against covid-19: commentary and mathematical modeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764932/
https://www.ncbi.nlm.nih.gov/pubmed/35040706
http://dx.doi.org/10.1128/mbio.03789-21
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