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dc.contributor.authorSunagawa, Junyaen
dc.contributor.authorPark, Hyeongkien
dc.contributor.authorKim, Kwang Suen
dc.contributor.authorKomorizono, Ryoen
dc.contributor.authorChoi, Sooyounen
dc.contributor.authorRamirez Torres, Luciaen
dc.contributor.authorWoo, Joohyeonen
dc.contributor.authorJeong, Yong Damen
dc.contributor.authorHart, William S.en
dc.contributor.authorThompson, Robin N.en
dc.contributor.authorAihara, Kazuyukien
dc.contributor.authorIwami, Shingoen
dc.contributor.authorYamaguchi, Ryoen
dc.contributor.alternative砂川, 純也ja
dc.contributor.alternativeパク, ヒョンギja
dc.contributor.alternative小森園, 亮ja
dc.contributor.alternative合原, 一幸ja
dc.contributor.alternative岩見, 真吾ja
dc.contributor.alternative山口, 諒ja
dc.date.accessioned2023-11-28T02:15:27Z-
dc.date.available2023-11-28T02:15:27Z-
dc.date.issued2023-11-21-
dc.identifier.urihttp://hdl.handle.net/2433/286186-
dc.descriptionAI技術で新型コロナウイルスの進化メカニズムを分析 --ウイルスの進化予測を踏まえた感染症対策の第一歩--. 京都大学プレスリリース. 2023-11-22.ja
dc.descriptionArticles: Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution. 京都大学プレスリリース. 2023-11-22.en
dc.description.abstractDuring the COVID-19 pandemic, human behavior change as a result of nonpharmaceutical interventions such as isolation may have induced directional selection for viral evolution. By combining previously published empirical clinical data analysis and multi-level mathematical modeling, we find that the SARS-CoV-2 variants selected for as the virus evolved from the pre-Alpha to the Delta variant had earlier and higher peak in viral load dynamics but a shorter duration of infection. Selection for increased transmissibility shapes the viral load dynamics, and the isolation measure is likely to be a driver of these evolutionary transitions. In addition, we show that a decreased incubation period and an increased proportion of asymptomatic infection are also positively selected for as SARS-CoV-2 mutated to adapt to human behavior (i.e., Omicron variants). The quantitative information and predictions we present here can guide future responses in the potential arms race between pandemic interventions and viral evolution.en
dc.language.isoeng-
dc.publisherSpringer Natureen
dc.rights© The Author(s) 2023en
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/-
dc.subjectEvolutionary ecologyen
dc.subjectPopulation dynamicsen
dc.subjectViral infectionen
dc.titleIsolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolutionen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleNature Communicationsen
dc.identifier.volume14-
dc.relation.doi10.1038/s41467-023-43043-2-
dc.textversionpublisher-
dc.identifier.artnum7395-
dc.addressDepartment of Advanced Transdisciplinary Sciences, Hokkaido Universityen
dc.addressinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya Universityen
dc.addressinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Department of Scientific Computing, Pukyong National University; Department of Mathematics, Pusan National Universityen
dc.addressLaboratory of RNA Viruses, Department of Virus Research, Institute for Life and Medical Sciences (LiMe), Kyoto Universityen
dc.addressinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Department of Mathematics, Pusan National Universityen
dc.addressinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya Universityen
dc.addressinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya Universityen
dc.addressinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Department of Mathematics, Pusan National Universityen
dc.addressMathematical Institute, University of Oxforden
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.addressInternational Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyoen
dc.addressinterdisciplinary Biology Laboratory (iBLab), 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 (ASHBi), Kyoto University; Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), RIKEN; NEXT-Ganken Program, Japanese Foundation for Cancer Research (JFCR); Science Groove Incen
dc.addressDepartment of Advanced Transdisciplinary Sciences, Hokkaido University; Department of Zoology & Biodiversity Research Centre, University of British Columbiaen
dc.identifier.pmid37989736-
dc.relation.urlhttps://ashbi.kyoto-u.ac.jp/ja/news/20231122_research-result_shingo-iwami/-
dc.relation.urlhttps://ashbi.kyoto-u.ac.jp/news/20231122_research-result_shingo-iwami/-
dcterms.accessRightsopen access-
datacite.awardNumber22H05215-
datacite.awardNumber18H01139-
datacite.awardNumber16H04845-
datacite.awardNumber21K15160-
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-PROJECT-21K15160/-
dc.identifier.eissn2041-1723-
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生殖隔離における種間非対称性の進化生態学的起源ja
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