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Australian state influenza notifications and school holiday closures in 2019

Background: The impact of school holidays on influenza rates has been sparsely documented in Australia. In 2019, the early winter influenza season coincided with mid-year school breaks, enabling us the unusual opportunity to examine how influenza incidence changed during school holiday closure dates...

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Autores principales: Scott, Anna Mae, Bakhit, Mina, Clark, Justin, Vermeulen, Melanie, Jones, Mark, Looke, David, Del Mar, Chris, Glasziou, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097737/
https://www.ncbi.nlm.nih.gov/pubmed/33976871
http://dx.doi.org/10.12688/f1000research.21145.3
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author Scott, Anna Mae
Bakhit, Mina
Clark, Justin
Vermeulen, Melanie
Jones, Mark
Looke, David
Del Mar, Chris
Glasziou, Paul
author_facet Scott, Anna Mae
Bakhit, Mina
Clark, Justin
Vermeulen, Melanie
Jones, Mark
Looke, David
Del Mar, Chris
Glasziou, Paul
author_sort Scott, Anna Mae
collection PubMed
description Background: The impact of school holidays on influenza rates has been sparsely documented in Australia. In 2019, the early winter influenza season coincided with mid-year school breaks, enabling us the unusual opportunity to examine how influenza incidence changed during school holiday closure dates. Methods: The weekly influenza data from five Australian state and one territory health departments for the period of week 19 (mid-May) to week 39 (early October) 2019 were compared to each state’s public-school holiday closure dates. We used segmented regression to model the weekly counts and a negative binomial distribution to account for overdispersion due to autocorrelation. The models’ goodness-of-fit was assessed by plots of observed versus expected counts, plots of residuals versus predicted values, and Pearson’s Chi-square test. The main exposure was the July two-week school holiday period, using a lag of one week. The effect is estimated as a percent change in incidence level, and in slope. Results: School holidays were associated with significant declines in influenza incidence in three states and one territory by between 41% and 65%. Two states did not show evidence of declines although one of those states had already passed its peak by the time of the school holidays. The models showed acceptable goodness-of-fit. The first decline during school holidays is seen in the school aged (5-19 years) population, with the declines in the adult and infant populations being smaller and following a week later. Conclusions: Given the significant and rapid reductions in incidence, these results have important public health implications. Closure or extension of holiday periods could be an emergency option for state governments.
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spelling pubmed-80977372021-05-10 Australian state influenza notifications and school holiday closures in 2019 Scott, Anna Mae Bakhit, Mina Clark, Justin Vermeulen, Melanie Jones, Mark Looke, David Del Mar, Chris Glasziou, Paul F1000Res Research Article Background: The impact of school holidays on influenza rates has been sparsely documented in Australia. In 2019, the early winter influenza season coincided with mid-year school breaks, enabling us the unusual opportunity to examine how influenza incidence changed during school holiday closure dates. Methods: The weekly influenza data from five Australian state and one territory health departments for the period of week 19 (mid-May) to week 39 (early October) 2019 were compared to each state’s public-school holiday closure dates. We used segmented regression to model the weekly counts and a negative binomial distribution to account for overdispersion due to autocorrelation. The models’ goodness-of-fit was assessed by plots of observed versus expected counts, plots of residuals versus predicted values, and Pearson’s Chi-square test. The main exposure was the July two-week school holiday period, using a lag of one week. The effect is estimated as a percent change in incidence level, and in slope. Results: School holidays were associated with significant declines in influenza incidence in three states and one territory by between 41% and 65%. Two states did not show evidence of declines although one of those states had already passed its peak by the time of the school holidays. The models showed acceptable goodness-of-fit. The first decline during school holidays is seen in the school aged (5-19 years) population, with the declines in the adult and infant populations being smaller and following a week later. Conclusions: Given the significant and rapid reductions in incidence, these results have important public health implications. Closure or extension of holiday periods could be an emergency option for state governments. F1000 Research Limited 2021-05-26 /pmc/articles/PMC8097737/ /pubmed/33976871 http://dx.doi.org/10.12688/f1000research.21145.3 Text en Copyright: © 2021 Scott AM et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Scott, Anna Mae
Bakhit, Mina
Clark, Justin
Vermeulen, Melanie
Jones, Mark
Looke, David
Del Mar, Chris
Glasziou, Paul
Australian state influenza notifications and school holiday closures in 2019
title Australian state influenza notifications and school holiday closures in 2019
title_full Australian state influenza notifications and school holiday closures in 2019
title_fullStr Australian state influenza notifications and school holiday closures in 2019
title_full_unstemmed Australian state influenza notifications and school holiday closures in 2019
title_short Australian state influenza notifications and school holiday closures in 2019
title_sort australian state influenza notifications and school holiday closures in 2019
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097737/
https://www.ncbi.nlm.nih.gov/pubmed/33976871
http://dx.doi.org/10.12688/f1000research.21145.3
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