TY - JOUR

T1 - Commentary on the use of the reproduction number R during the COVID-19 pandemic

AU - Vegvari, Carolin

AU - Abbott, Sam

AU - Ball, Frank

AU - Brooks-Pollock, Ellen

AU - Challen, Robert

AU - Collyer, Benjamin S.

AU - Dangerfield, Ciara

AU - Gog, Julia R.

AU - Gostic, Katelyn M.

AU - Heffernan, Jane M.

AU - Hollingsworth, T. Deirdre

AU - Isham, Valerie

AU - Kenah, Eben

AU - Mollison, Denis

AU - Panovska-Griffiths, Jasmina

AU - Pellis, Lorenzo

AU - Roberts, Michael G.

AU - Tomba, Gianpaolo Scalia

AU - Thompson, Robin N.

AU - Trapman, Pieter

N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research and/or authorship of this article: This work was supported by EPSRC grant no EP/R014604/1. EBP acknowledges funding from the Medical Research Council (MRC) (MC/PC/19067) and the NIHR Health Protection Research Unit in Behavioural Science and Evaluation at the University of Bristol. Support for RC’s research is provided by the EPSRC via grant EP/N014391/1, RC is also funded by the NHS Global Digital Exemplar programme (GDE). JMH acknowledges funding from the Natural Science and Engineering Research Council of Canada (NSERC), Canadian Institutes for Health Research (CIHR). MGR is supported by the Marsden Fund under contract MAU1718. GPST acknowledges the MIUR Excellence Department Project awarded to the Department of Mathematics, University of Rome Tor Vergata, CUP E83C18000100006. LP acknowledges the Wellcome Trust and the Royal Society (grant 202562/Z/16/Z) for funding. EK was supported by the National Institute of Allergy and Infectious Diseases (NIAID) grant R01 AI116770. PT acknowledges Vetenskapsrådet (Swedish Research Council), grant 2016-04566. KMG acknowledges fellowship support from the James S. McDonnell Foundation. The contents are solely the responsibility of the authors and do not necessarily represent the official views of NIAID or the US National Institute of Health.
Funding Information:
The authors would like to thank the Isaac Newton Institute for Mathematical Sciences, Cambridge, for support and hospitality during the programme Infectious Dynamics of Pandemics where work on this paper was undertaken. This work was supported by EPSRC grant no EP/R014604/1. EBP acknowledges funding from the Medical Research Council.
Publisher Copyright:
© The Author(s) 2021.

PY - 2021/9/27

Y1 - 2021/9/27

N2 - Since the beginning of the COVID-19 pandemic, the reproduction number (Formula presented.) has become a popular epidemiological metric used to communicate the state of the epidemic. At its most basic, (Formula presented.) is defined as the average number of secondary infections caused by one primary infected individual. (Formula presented.) seems convenient, because the epidemic is expanding if (Formula presented.) and contracting if (Formula presented.). The magnitude of (Formula presented.) indicates by how much transmission needs to be reduced to control the epidemic. Using (Formula presented.) in a naïve way can cause new problems. The reasons for this are threefold: (1) There is not just one definition of (Formula presented.) but many, and the precise definition of (Formula presented.) affects both its estimated value and how it should be interpreted. (2) Even with a particular clearly defined (Formula presented.), there may be different statistical methods used to estimate its value, and the choice of method will affect the estimate. (3) The availability and type of data used to estimate (Formula presented.) vary, and it is not always clear what data should be included in the estimation. In this review, we discuss when (Formula presented.) is useful, when it may be of use but needs to be interpreted with care, and when it may be an inappropriate indicator of the progress of the epidemic. We also argue that careful definition of (Formula presented.), and the data and methods used to estimate it, can make (Formula presented.) a more useful metric for future management of the epidemic.

AB - Since the beginning of the COVID-19 pandemic, the reproduction number (Formula presented.) has become a popular epidemiological metric used to communicate the state of the epidemic. At its most basic, (Formula presented.) is defined as the average number of secondary infections caused by one primary infected individual. (Formula presented.) seems convenient, because the epidemic is expanding if (Formula presented.) and contracting if (Formula presented.). The magnitude of (Formula presented.) indicates by how much transmission needs to be reduced to control the epidemic. Using (Formula presented.) in a naïve way can cause new problems. The reasons for this are threefold: (1) There is not just one definition of (Formula presented.) but many, and the precise definition of (Formula presented.) affects both its estimated value and how it should be interpreted. (2) Even with a particular clearly defined (Formula presented.), there may be different statistical methods used to estimate its value, and the choice of method will affect the estimate. (3) The availability and type of data used to estimate (Formula presented.) vary, and it is not always clear what data should be included in the estimation. In this review, we discuss when (Formula presented.) is useful, when it may be of use but needs to be interpreted with care, and when it may be an inappropriate indicator of the progress of the epidemic. We also argue that careful definition of (Formula presented.), and the data and methods used to estimate it, can make (Formula presented.) a more useful metric for future management of the epidemic.

KW - COVID-19 pandemic

KW - Reproduction number

U2 - 10.1177/09622802211037079

DO - 10.1177/09622802211037079

M3 - Article

SN - 0962-2802

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

ER -