{"title":"SARS-CoV-2 transmission in university classes.","authors":"William Ruth, Richard Lockhart","doi":"10.1007/s13721-022-00375-1","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s13721-022-00375-1.</p>","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":" ","pages":"32"},"PeriodicalIF":2.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9419647/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Network Modeling and Analysis in Health Informatics and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13721-022-00375-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/8/27 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
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.
期刊介绍：
NetMAHIB publishes original research articles and reviews reporting how graph theory, statistics, linear algebra and machine learning techniques can be effectively used for modelling and analysis in health informatics and bioinformatics. It aims at creating a synergy between these disciplines by providing a forum for disseminating the latest developments and research findings; hence, results can be shared with readers across institutions, governments, researchers, students, and the industry. The journal emphasizes fundamental contributions on new methodologies, discoveries and techniques that have general applicability and which form the basis for network based modelling, knowledge discovery, knowledge sharing and decision support to the benefit of patients, healthcare professionals and society in traditional and advanced emerging settings, including eHealth and mHealth .
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