Estimation of Reproduction Numbers in Real Time: Conceptual and Statistical Challenges

Lorenzo Pellis; Paul J. Birrell; Joshua Blake; Christopher E. Overton; Francesca Scarabel; Helena B. Stage; Ellen Brooks-Pollock; Leon Danon; Ian Hall; Thomas A. House; Matt J. Keeling; Jonathan M. Read; Daniela De Angelis

doi:10.1111/rssa.12955

journal article Open Access Nov 01, 2022

Estimation of Reproduction Numbers in Real Time: Conceptual and Statistical Challenges

Lorenzo Pellis Paul J. Birrell Joshua Blake Christopher E. Overton Francesca Scarabel Helena B. Stage Ellen Brooks-Pollock Leon Danon Ian Hall Thomas A. House Matt J. Keeling

Jonathan M. Read Daniela De Angelis

Journal of the Royal Statistical Society Series A: Statistics in Society Vol. 185 No. Supplement_1 pp. S112-S130 · Oxford University Press (OUP)

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Abstract

Abstract
The reproduction number R has been a central metric of the COVID-19 pandemic response, published weekly by the UK government and regularly reported in the media. Here, we provide a formal definition and discuss the advantages and most common misconceptions around this quantity. We consider the intuition behind different formulations of R, the complexities in its estimation (including the unavoidable lags involved), and its value compared to other indicators (e.g. the growth rate) that can be directly observed from aggregate surveillance data and react more promptly to changes in epidemic trend. As models become more sophisticated, with age and/or spatial structure, formulating R becomes increasingly complicated and inevitably model-dependent. We present some models currently used in the UK pandemic response as examples. Ultimately, limitations in the available data streams, data quality and time constraints force pragmatic choices to be made on a quantity that is an average across time, space, social structure and settings. Effectively communicating these challenges is important but often difficult in an emergency.

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Citations

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References

Details

Published: Nov 01, 2022
Vol/Issue: 185(Supplement_1)
Pages: S112-S130
License: View

Authors

Christopher E. Overton

The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), The University of Warwick, Coventry CV4 7AL, UK

Funding

Wellcome Trust Award: 202562/Z/16/Z

Medical Research Council Award: MC UU 00002/11

Royal Society Award: INF∖R2∖180067

Engineering and Physical Sciences Research Council Award: EP/N510129/1

Alexander von Humboldt-Stiftung

Economic and Social Research Council

Alan Turing Institute

National Institute for Health Research

National Institute for Health Research Health Protection Research Unit Award: NIHR200877

Cite This Article

Lorenzo Pellis, Paul J. Birrell, Joshua Blake, et al. (2022). Estimation of Reproduction Numbers in Real Time: Conceptual and Statistical Challenges. Journal of the Royal Statistical Society Series A: Statistics in Society, 185(Supplement_1), S112-S130. https://doi.org/10.1111/rssa.12955

Estimation of Reproduction Numbers in Real Time: Conceptual and Statistical Challenges

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