EpiBeds: Data informed modelling of the COVID-19 hospital burden in England

Overton, C.E. orcid.org/0000-0002-8433-4010, Pellis, L., Stage, H.B. orcid.org/0000-0001-9938-8452 et al. (9 more authors) (2022) EpiBeds: Data informed modelling of the COVID-19 hospital burden in England. PLOS Computational Biology, 18 (9). ARTN e1010406. ISSN 1553-734X

Abstract

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Item Type: Article
Authors/Creators:
Editors:
  • Struchiner, C.J.
Copyright, Publisher and Additional Information:

© 2022 Overton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Keywords: Humans; Hospitalization; Hospitals; England; Pandemics; COVID-19
Dates:
  • Published: 6 September 2022
  • Published (online): 6 September 2022
  • Accepted: 18 July 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 29 Jan 2024 14:28
Last Modified: 29 Jan 2024 14:28
Published Version: https://journals.plos.org/ploscompbiol/article?id=...
Status: Published
Publisher: Public Library of Science (PLoS)
Identification Number: 10.1371/journal.pcbi.1010406
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