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Comparison of the 2021 COVID-19 roadmap projections against public health data in England
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Keeling, Matthew James, Dyson, Louise, Tildesley, Michael J., Hill, Edward M. and Moore, Sam (2022) Comparison of the 2021 COVID-19 roadmap projections against public health data in England. Nature Communications, 13 . 4924. doi:10.1038/s41467-022-31991-0 ISSN 2041-1723. [ 🗎 Public]. [ (✓) hoa:511 ]
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WRAP-Comparison-2021-COVID-19-roadmap-public-health-data-England-22.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (2823Kb) | Preview |
Official URL: https://doi.org/10.1038/s41467-022-31991-0
Abstract
Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.
| Item Type: | Journal Article | ||||||||||||
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| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Science > Mathematics |
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| Library of Congress Subject Headings (LCSH): | COVID-19 Pandemic, 2020- -- Government policy -- Great Britain, COVID-19 Pandemic, 2020- -- Mathematical models, COVID-19 (Disease) -- Transmission -- Mathematical models, COVID-19 (Disease) -- Prevention -- Government policy -- Great Britain | ||||||||||||
| Journal or Publication Title: | Nature Communications | ||||||||||||
| Publisher: | Nature Publishing Group | ||||||||||||
| ISSN: | 2041-1723 | ||||||||||||
| Official Date: | 22 August 2022 | ||||||||||||
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| Volume: | 13 | ||||||||||||
| Article Number: | 4924 | ||||||||||||
| DOI: | 10.1038/s41467-022-31991-0 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
| Date of first compliant deposit: | 24 August 2022 | ||||||||||||
| Date of first compliant Open Access: | 24 August 2022 | ||||||||||||
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