ArticlePLoS computational biology2022
EpiBeds: Data informed modelling of the COVID-19 hospital burden in England.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Non-centering for discrete-valued state transition models: an application to ESBL-producingStatistics and computing · 2026Article
- A modular approach to forecasting COVID-19 hospital bed occupancy.Communications medicine · 2025Article
- Time-varying reproduction number estimation: fusing compartmental models with generalized additive models.Journal of the Royal Society, Interface · 2025Article
- Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England.Royal Society open science · 2024Article
- Large-scale real-life implementation of technology-enabled care to maximize hospitals' medical surge preparedness during future infectious disease outbreaks and winter seasons: a viewpoint.Frontiers in public health · 2023Article
- Estimation of reproduction numbers in real time: Conceptual and statistical challenges.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2022Article
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Authors and funding
12 authors.
Funding
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.
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Registered trials
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