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

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 pr

SUBMITTER: Overton CE 

PROVIDER: S-EPMC9481171 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature