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Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions
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dc.contributor.author | Panovska-Griffiths, J. | |
dc.contributor.author | Swallow, B. | |
dc.contributor.author | Hinch, R. | |
dc.contributor.author | Cohen, J. | |
dc.contributor.author | Rosenfeld, K. | |
dc.contributor.author | Stuart, R. M. | |
dc.contributor.author | Ferretti, L. | |
dc.contributor.author | Di Lauro, F. | |
dc.contributor.author | Wymant, C. | |
dc.contributor.author | Izzo, A. | |
dc.contributor.author | Waites, W. | |
dc.contributor.author | Viner, R. | |
dc.contributor.author | Bonell, C. | |
dc.contributor.author | Fraser, C. | |
dc.contributor.author | Klein, D. | |
dc.contributor.author | Kerr, C. C. | |
dc.contributor.author | The COVID-19 Genomics UK (COG-UK) Consortium | |
dc.date.accessioned | 2022-09-28T12:30:20Z | |
dc.date.available | 2022-09-28T12:30:20Z | |
dc.date.issued | 2022-10-03 | |
dc.identifier | 281142519 | |
dc.identifier | e5e2693a-23cf-4210-82f4-a45d1418dd76 | |
dc.identifier | 85134371098 | |
dc.identifier.citation | Panovska-Griffiths , J , Swallow , B , Hinch , R , Cohen , J , Rosenfeld , K , Stuart , R M , Ferretti , L , Di Lauro , F , Wymant , C , Izzo , A , Waites , W , Viner , R , Bonell , C , Fraser , C , Klein , D , Kerr , C C & The COVID-19 Genomics UK (COG-UK) Consortium 2022 , ' Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions ' , Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences , vol. 380 , no. 2233 , 20210315 . https://doi.org/10.1098/rsta.2021.0315 | en |
dc.identifier.issn | 1364-503X | |
dc.identifier.other | crossref: 10.1098/rsta.2021.0315 | |
dc.identifier.other | ORCID: /0000-0002-0227-2160/work/118411956 | |
dc.identifier.uri | https://hdl.handle.net/10023/26094 | |
dc.description | J.P.G.’s work was supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care (DHSC). This work was also supported by DHSC funding awarded to C.F. and Li Ka Shing Foundation grant awarded to C.F. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) (grant code: MC_PC_19027), and Genome Research Limited, operating as the Wellcome Sanger Institute. | en |
dc.description.abstract | The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and the agent-based model Covasim, in June 2021, to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50–80% more transmissible than B.1.177 and Delta to be 65–90% more transmissible than Alpha. Using these estimates in Covasim (calibrated 1 September 2020 to 20 June 2021), in June 2021, we found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination. | |
dc.format.extent | 19 | |
dc.format.extent | 1543735 | |
dc.language.iso | eng | |
dc.relation.ispartof | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | en |
dc.subject | Multivariateregression modelling | en |
dc.subject | COVID-19 | en |
dc.subject | Agent-based modelling | en |
dc.subject | HA Statistics | en |
dc.subject | RA0421 Public health. Hygiene. Preventive Medicine | en |
dc.subject | 3rd-DAS | en |
dc.subject | SDG 3 - Good Health and Well-being | en |
dc.subject.lcc | HA | en |
dc.subject.lcc | RA0421 | en |
dc.title | Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions | en |
dc.type | Journal article | en |
dc.contributor.institution | University of St Andrews. School of Mathematics and Statistics | en |
dc.contributor.institution | University of St Andrews. Centre for Research into Ecological & Environmental Modelling | en |
dc.identifier.doi | 10.1098/rsta.2021.0315 | |
dc.description.status | Peer reviewed | en |
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