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Modelling the impact of the Omicron BA.5 subvariant in New Zealand

New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in early 2022, which occurred against a backdrop of high two-dose vaccination rates, ongoing roll-out of boosters and paediatric doses, and negligible levels of prior infection. New Omicron subvariants have subsequently emerged with...

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Autores principales: Lustig, Audrey, Vattiato, Giorgia, Maclaren, Oliver, Watson, Leighton M., Datta, Samik, Plank, Michael J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890098/
https://www.ncbi.nlm.nih.gov/pubmed/36722072
http://dx.doi.org/10.1098/rsif.2022.0698
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author Lustig, Audrey
Vattiato, Giorgia
Maclaren, Oliver
Watson, Leighton M.
Datta, Samik
Plank, Michael J.
author_facet Lustig, Audrey
Vattiato, Giorgia
Maclaren, Oliver
Watson, Leighton M.
Datta, Samik
Plank, Michael J.
author_sort Lustig, Audrey
collection PubMed
description New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in early 2022, which occurred against a backdrop of high two-dose vaccination rates, ongoing roll-out of boosters and paediatric doses, and negligible levels of prior infection. New Omicron subvariants have subsequently emerged with a significant growth advantage over the previously dominant BA.2. We investigated a mathematical model that included waning of vaccine-derived and infection-derived immunity, as well as the impact of the BA.5 subvariant which began spreading in New Zealand in May 2022. The model was used to provide scenarios to the New Zealand Government with differing levels of BA.5 growth advantage, helping to inform policy response and healthcare system preparedness during the winter period. In all scenarios investigated, the projected peak in new infections during the BA.5 wave was smaller than in the first Omicron wave in March 2022. However, results indicated that the peak hospital occupancy was likely to be higher than in March 2022, primarily due to a shift in the age distribution of infections to older groups. We compare model results with subsequent epidemiological data and show that the model provided a good projection of cases, hospitalizations and deaths during the BA.5 wave.
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spelling pubmed-98900982023-02-03 Modelling the impact of the Omicron BA.5 subvariant in New Zealand Lustig, Audrey Vattiato, Giorgia Maclaren, Oliver Watson, Leighton M. Datta, Samik Plank, Michael J. J R Soc Interface Life Sciences–Mathematics interface New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in early 2022, which occurred against a backdrop of high two-dose vaccination rates, ongoing roll-out of boosters and paediatric doses, and negligible levels of prior infection. New Omicron subvariants have subsequently emerged with a significant growth advantage over the previously dominant BA.2. We investigated a mathematical model that included waning of vaccine-derived and infection-derived immunity, as well as the impact of the BA.5 subvariant which began spreading in New Zealand in May 2022. The model was used to provide scenarios to the New Zealand Government with differing levels of BA.5 growth advantage, helping to inform policy response and healthcare system preparedness during the winter period. In all scenarios investigated, the projected peak in new infections during the BA.5 wave was smaller than in the first Omicron wave in March 2022. However, results indicated that the peak hospital occupancy was likely to be higher than in March 2022, primarily due to a shift in the age distribution of infections to older groups. We compare model results with subsequent epidemiological data and show that the model provided a good projection of cases, hospitalizations and deaths during the BA.5 wave. The Royal Society 2023-02-01 /pmc/articles/PMC9890098/ /pubmed/36722072 http://dx.doi.org/10.1098/rsif.2022.0698 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
Lustig, Audrey
Vattiato, Giorgia
Maclaren, Oliver
Watson, Leighton M.
Datta, Samik
Plank, Michael J.
Modelling the impact of the Omicron BA.5 subvariant in New Zealand
title Modelling the impact of the Omicron BA.5 subvariant in New Zealand
title_full Modelling the impact of the Omicron BA.5 subvariant in New Zealand
title_fullStr Modelling the impact of the Omicron BA.5 subvariant in New Zealand
title_full_unstemmed Modelling the impact of the Omicron BA.5 subvariant in New Zealand
title_short Modelling the impact of the Omicron BA.5 subvariant in New Zealand
title_sort modelling the impact of the omicron ba.5 subvariant in new zealand
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890098/
https://www.ncbi.nlm.nih.gov/pubmed/36722072
http://dx.doi.org/10.1098/rsif.2022.0698
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