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dc.contributor.authorHart, William S.en
dc.contributor.authorPark, Hyeongkien
dc.contributor.authorJeong, Yong Damen
dc.contributor.authorKim, Kwang Suen
dc.contributor.authorYoshimura, Raikien
dc.contributor.authorThompson, Robin N.en
dc.contributor.authorIwami, Shingoen
dc.contributor.alternative吉村, 雷輝ja
dc.contributor.alternative岩見, 真吾ja
dc.date.accessioned2023-10-11T02:24:15Z-
dc.date.available2023-10-11T02:24:15Z-
dc.date.issued2023-10-10-
dc.identifier.urihttp://hdl.handle.net/2433/285496-
dc.description世界初・新型コロナウイルス感染によるクラスター発生確率の計算に成功 --数理モデルに基づく効果的な感染症対策の確立へ重要な一歩--. 京都大学プレスリリース. 2023-10-05.ja
dc.description.abstractIn the era of living with COVID-19, the risk of localised SARS-CoV-2 outbreaks remains. Here, we develop a multiscale modelling framework for estimating the local outbreak risk for a viral disease (the probability that a major outbreak results from a single case introduced into the population), accounting for within-host viral dynamics. Compared to population-level models previously used to estimate outbreak risks, our approach enables more detailed analysis of how the risk can be mitigated through pre-emptive interventions such as antigen testing. Considering SARS-CoV-2 as a case study, we quantify the within-host dynamics using data from individuals with omicron variant infections. We demonstrate that regular antigen testing reduces, but may not eliminate, the outbreak risk, depending on characteristics of local transmission. In our baseline analysis, daily antigen testing reduces the outbreak risk by 45% compared to a scenario without antigen testing. Additionally, we show that accounting for heterogeneity in within-host dynamics between individuals affects outbreak risk estimates and assessments of the impact of antigen testing. Our results therefore highlight important factors to consider when using multiscale models to design pre-emptive interventions against SARS-CoV-2 and other viruses.en
dc.language.isoeng-
dc.publisherProceedings of the National Academy of Sciencesen
dc.rightsCopyright © 2023 the Author(s). Published by PNAS.en
dc.rightsThis open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectINFECTIOUS DISEASE MODELLINGen
dc.subjectOUTBREAK RISKen
dc.subjectSARS-COV-2en
dc.subjectCOVID-19en
dc.subjectANTIGEN TESTINGen
dc.titleAnalysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case studyen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleProceedings of the National Academy of Sciences of the United States of Americaen
dc.identifier.volume120-
dc.identifier.issue41-
dc.relation.doi10.1073/pnas.2305451120-
dc.textversionpublisher-
dc.identifier.artnume2305451120-
dc.addressMathematical Institute, University of Oxford; lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya Universityen
dc.addresslnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya Universityen
dc.addresslnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University; Department of Mathematics, Pusan National Universityen
dc.addresslnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University; Department of Scientific Computing, Pukyong National Universityen
dc.addresslnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya Universityen
dc.addressMathematical Institute, University of Oxford; Mathematics Institute, University of Warwick; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwicken
dc.addresslnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University; Institute of Mathematics for Industry, Kyushu University; Institute for the Advanced Study of Human Biology, Kyoto University; Interdisciplinary Theoretical and Mathematical Sciences Program, RIKEN; NEXT- Ganken Program, Japanese Foundation for Cancer Research; Science Groove Inc.en
dc.identifier.pmid37788317-
dc.relation.urlhttps://ashbi.kyoto-u.ac.jp/ja/news/20231005_research-result_shingo-iwami/-
dcterms.accessRightsopen access-
datacite.awardNumber22H05215-
datacite.awardNumber18H01139-
datacite.awardNumber16H04845-
datacite.awardNumber20H05042-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-22H05215/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18H01139/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-16H04845/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-20H05042/-
dc.identifier.pissn0027-8424-
dc.identifier.eissn1091-6490-
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitle異分野融合研究で解明するコロナ禍の当事者化ja
jpcoar.awardTitle生命科学におけるパターン形成の新しいモデルと数学的解析手法の確立ja
jpcoar.awardTitle遺伝子配列に刻まれた宿主と病原体の攻防を読み解くビックデータ生態学の創成ja
jpcoar.awardTitle造血幹細胞老化により変容する細胞ダイバーシティの数理科学的解析ja
出現コレクション:学術雑誌掲載論文等

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