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

Abstract

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 R estimate 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 biases and limitations associated with a single source of data. We discuss how R can be generated from different data sources and show that it is a good summary indicator of the current dynamics in an epidemic.

Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England

“…As we discussed in our previous paper [ 22 ], the value in getting a combined forecast from across models and datasets is not only just in the weighted averaging of those estimates but also in the formation of a community that is constantly discussing the outcomes, the modelling assumptions and the input data, identifying the drivers behind the differences across models’ outcomes when formulating the aggregated possible future projections.…”