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SARS-CoV-2 transmission in university classes

We investigate transmission dynamics for SARS-CoV-2 on a real network of classes at Simon Fraser University. Outbreaks are simulated over the course of one semester across numerous parameter settings, including moving classes above certain size thresholds online. Regression trees are used to analyze...

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Detalles Bibliográficos
Autores principales: Ruth, William, Lockhart, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9419647/
https://www.ncbi.nlm.nih.gov/pubmed/36061223
http://dx.doi.org/10.1007/s13721-022-00375-1
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author Ruth, William
Lockhart, Richard
author_facet Ruth, William
Lockhart, Richard
author_sort Ruth, William
collection PubMed
description We investigate transmission dynamics for SARS-CoV-2 on a real network of classes at Simon Fraser University. Outbreaks are simulated over the course of one semester across numerous parameter settings, including moving classes above certain size thresholds online. Regression trees are used to analyze the effect of disease parameters on simulation outputs. We find that an aggressive class size thresholding strategy is required to mitigate the risk of a large outbreak, and that transmission by symptomatic individuals is a key driver of outbreak size. These findings provide guidance for designing control strategies at other institutions, as well as setting priorities and allocating resources for disease monitoring. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13721-022-00375-1.
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spelling pubmed-94196472022-08-30 SARS-CoV-2 transmission in university classes Ruth, William Lockhart, Richard Netw Model Anal Health Inform Bioinform Original Article We investigate transmission dynamics for SARS-CoV-2 on a real network of classes at Simon Fraser University. Outbreaks are simulated over the course of one semester across numerous parameter settings, including moving classes above certain size thresholds online. Regression trees are used to analyze the effect of disease parameters on simulation outputs. We find that an aggressive class size thresholding strategy is required to mitigate the risk of a large outbreak, and that transmission by symptomatic individuals is a key driver of outbreak size. These findings provide guidance for designing control strategies at other institutions, as well as setting priorities and allocating resources for disease monitoring. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13721-022-00375-1. Springer Vienna 2022-08-27 2022 /pmc/articles/PMC9419647/ /pubmed/36061223 http://dx.doi.org/10.1007/s13721-022-00375-1 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Ruth, William
Lockhart, Richard
SARS-CoV-2 transmission in university classes
title SARS-CoV-2 transmission in university classes
title_full SARS-CoV-2 transmission in university classes
title_fullStr SARS-CoV-2 transmission in university classes
title_full_unstemmed SARS-CoV-2 transmission in university classes
title_short SARS-CoV-2 transmission in university classes
title_sort sars-cov-2 transmission in university classes
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9419647/
https://www.ncbi.nlm.nih.gov/pubmed/36061223
http://dx.doi.org/10.1007/s13721-022-00375-1
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