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

Overton, Christopher E. and Pellis, Lorenzo and Stage, Helena B. and Scarabel, Francesca and Burton, Joshua and Fraser, Christophe and Hall, Ian and House, Thomas A. and Jewell, Chris and Nurtay, Anel and Pagani, Filippo and Lythgoe, Katrina A. (2022) EpiBeds:Data informed modelling of the COVID-19 hospital burden in England. PLoS Computational Biology, 18 (9). ISSN 1553-734X

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Abstract

The first year of the COVID-19 pandemic put considerable strain on healthcare systems worldwide. In order to predict the effect of the local epidemic on hospital capacity in England, we used a variety of data streams to inform the construction and parameterisation of a hospital progression model, EpiBeds, which was coupled to a model of the generalised epidemic. In this model, individuals progress through different pathways (e.g. may recover, die, or progress to intensive care and recover or die) and data from a partially complete patient-pathway line-list was used to provide initial estimates of the mean duration that individuals spend in the different hospital compartments. We then fitted EpiBeds using complete data on hospital occupancy and hospital deaths, enabling estimation of the proportion of individuals that follow the different clinical pathways, the reproduction number of the generalised epidemic, and to make short-term predictions of hospital bed demand. The construction of EpiBeds makes it straightforward to adapt to different patient pathways and settings beyond England. As part of the UK response to the pandemic, EpiBeds provided weekly forecasts to the NHS for hospital bed occupancy and admissions in England, Wales, Scotland, and Northern Ireland at national and regional scales.

Item Type:
Journal Article
Journal or Publication Title:
PLoS Computational Biology
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1300/1312
Subjects:
?? RESEARCH ARTICLEMEDICINE AND HEALTH SCIENCESPEOPLE AND PLACESRESEARCH AND ANALYSIS METHODSPHYSICAL SCIENCESBIOLOGY AND LIFE SCIENCESECOLOGYCELLULAR AND MOLECULAR NEUROSCIENCEECOLOGY, EVOLUTION, BEHAVIOR AND SYSTEMATICSGENETICSMODELLING AND SIMULATIONCOMPU ??
ID Code:
176269
Deposited By:
Deposited On:
20 Sep 2022 09:00
Refereed?:
Yes
Published?:
Published
Last Modified:
13 Oct 2023 10:50