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完全メタデータレコード
DCフィールド | 値 | 言語 |
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dc.contributor.author | Murayama, Hiroaki | en |
dc.contributor.author | Kayano, Taishi | en |
dc.contributor.author | Nishiura, Hiroshi | en |
dc.contributor.alternative | 茅野, 大志 | ja |
dc.contributor.alternative | 西浦, 博 | ja |
dc.date.accessioned | 2022-11-25T05:53:31Z | - |
dc.date.available | 2022-11-25T05:53:31Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://hdl.handle.net/2433/277496 | - |
dc.description.abstract | [Background] In Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. [Methods] The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. [Results] The weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. [Conclusions] The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data. | en |
dc.language.iso | eng | - |
dc.publisher | BMC | en |
dc.publisher | Springer Nature | en |
dc.rights | © The Author(s) 2021. | en |
dc.rights | This 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.uri | http://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | Statistical estimation | en |
dc.subject | Mutation | en |
dc.subject | Transmissibility | en |
dc.subject | Coronavirus | en |
dc.subject | Epidemiological model | en |
dc.subject | Mathematical model | en |
dc.title | Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021 | en |
dc.type | journal article | - |
dc.type.niitype | Journal Article | - |
dc.identifier.jtitle | Theoretical Biology and Medical Modelling | en |
dc.identifier.volume | 18 | - |
dc.relation.doi | 10.1186/s12976-021-00146-x | - |
dc.textversion | publisher | - |
dc.identifier.artnum | 13 | - |
dc.identifier.pmid | 34273991 | - |
dcterms.accessRights | open access | - |
datacite.awardNumber | 17H04701 | - |
datacite.awardNumber | 21H03198 | - |
datacite.awardNumber | 21K10495 | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17H04701/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21H03198/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21K10495/ | - |
dc.identifier.eissn | 1742-4682 | - |
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 | 感染者隔離効果の推定手法開発と隔離の有効性メカニズムの解明 | ja |
jpcoar.awardTitle | 新型コロナウイルス感染症の異質性や不顕性を加味したリアルタイム評価研究基盤の構築 | ja |
jpcoar.awardTitle | COVID-19の2次感染に係る異質性を加味した効果的な制御戦略の定量化 | ja |
出現コレクション: | 学術雑誌掲載論文等 |

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