Combining models to generate a consensus effective reproduction number R for the COVID-19 epidemic status in England

Harrison Manley, Josie Park,Luke Bevan, Alberto Sanchez-Marroquin, Gabriel Danelian, Thomas Bayley, Veronica Bowman, Thomas Maishman,Thomas Finnie, Andre Charlett,Nicholas A. Watkins, Johanna Hutchinson, Graham Medley, Steven Riley,Jasmina Panovska-Griffiths

EPIDEMIOLOGY AND INFECTION(2024)

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摘要
The effective reproduction number R was widely accepted as a key indicator during the early stages of the COVID-19 pandemic. In the UK, the R value published on the UK Government Dashboard has been generated as a combined value from an ensemble of epidemiological models via a collaborative initiative between academia and government. In this paper, we outline this collaborative modelling approach and illustrate how, by using an established combination method, a combined Restimate can be generated from an ensemble of epidemiological models. We analyse the R values calculated for the period between April 2021 and December 2021, to show that this R is robust to different model weighting methods and ensemble sizes and that using heterogeneous data sources for validation increases its robustness and reduces the biasesand limitations associated with a single source of data. We discuss how R can be generated from different data sources and s how that it is a good summary indicator of the current dynamics in an epidemic
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关键词
COVID-19,reproduction number R,ensemble modelling,statistical analysis
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