In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 9 ( 2022-9-6), p. e1010406-
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.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1010406
DOI:
10.1371/journal.pcbi.1010406.g001
DOI:
10.1371/journal.pcbi.1010406.g002
DOI:
10.1371/journal.pcbi.1010406.g003
DOI:
10.1371/journal.pcbi.1010406.g004
DOI:
10.1371/journal.pcbi.1010406.t001
DOI:
10.1371/journal.pcbi.1010406.t002
DOI:
10.1371/journal.pcbi.1010406.t003
DOI:
10.1371/journal.pcbi.1010406.t004
DOI:
10.1371/journal.pcbi.1010406.t005
DOI:
10.1371/journal.pcbi.1010406.s001
DOI:
10.1371/journal.pcbi.1010406.s002
DOI:
10.1371/journal.pcbi.1010406.s003
DOI:
10.1371/journal.pcbi.1010406.r001
DOI:
10.1371/journal.pcbi.1010406.r002
DOI:
10.1371/journal.pcbi.1010406.r003
DOI:
10.1371/journal.pcbi.1010406.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2193340-6
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