Estimation of reproduction numbers in real time: Conceptual and statistical challenges

JUNIPER Consortium

doi:10.1111/rssa.12955

Estimation of reproduction numbers in real time: Conceptual and statistical challenges

JUNIPER Consortium

Statistics Unit

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

The reproduction number (Formula presented.) 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 (Formula presented.), 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 (Formula presented.) 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.

Original language	English
Pages (from-to)	S112-S130
Journal	Journal of the Royal Statistical Society. Series A: Statistics in Society
Volume	185
Issue number	S1
DOIs	https://doi.org/10.1111/rssa.12955
Publication status	Published - Nov 2022

Bibliographical note

Funding Information:
information Alan Turing Institute, Alexander von Humboldt-Stiftung, Economic and Social Research Council, Engineering and Physical Sciences Research Council, Grant/Award Numbers: EP/N510129/1; EP/V027468/1; EP/V051555/1; Medical Research Council, Grant/Award Numbers: MC UU 00002/11; MC/PC/19067; MR/V028456/1; MR/V038613/1; National Institute for Health Research, National Institute for Health Research Health Protection Research Unit, Grant/Award Number: NIHR200877; Royal Society, Grant/Award Number: INF∖R2∖180067; Wellcome Trust, Grant/Award Number: 202562/Z/16/ZThe authors are very grateful to Phillippa Spencer and the Defence Science and Technology Laboratory (DSTL) data provision team for the relentless data management and provision throughout the pandemic, which has been essential for real-time reproduction number and growth rate estimates.

Publisher Copyright:
© 2022 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.

Keywords

growth rate
real-time estimation
reproduction numbers

Access to Document

10.1111/rssa.12955

Cite this

@article{d9610de56cd547c9a612fc0f70ec8b8f,

title = "Estimation of reproduction numbers in real time: Conceptual and statistical challenges",

abstract = "The reproduction number (Formula presented.) 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 (Formula presented.), 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 (Formula presented.) 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.",

keywords = "growth rate, real-time estimation, reproduction numbers",

author = "Lorenzo Pellis and Birrell, {Paul J.} and Joshua Blake and Overton, {Christopher E.} and Francesca Scarabel and Stage, {Helena B.} and Ellen Brooks-Pollock and Leon Danon and Ian Hall and House, {Thomas A.} and Keeling, {Matt J.} and Read, {Jonathan M.} and {De Angelis}, Daniela and {JUNIPER Consortium}",

note = "Funding Information: information Alan Turing Institute, Alexander von Humboldt-Stiftung, Economic and Social Research Council, Engineering and Physical Sciences Research Council, Grant/Award Numbers: EP/N510129/1; EP/V027468/1; EP/V051555/1; Medical Research Council, Grant/Award Numbers: MC UU 00002/11; MC/PC/19067; MR/V028456/1; MR/V038613/1; National Institute for Health Research, National Institute for Health Research Health Protection Research Unit, Grant/Award Number: NIHR200877; Royal Society, Grant/Award Number: INF∖R2∖180067; Wellcome Trust, Grant/Award Number: 202562/Z/16/ZThe authors are very grateful to Phillippa Spencer and the Defence Science and Technology Laboratory (DSTL) data provision team for the relentless data management and provision throughout the pandemic, which has been essential for real-time reproduction number and growth rate estimates. Publisher Copyright: {\textcopyright} 2022 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.",

year = "2022",

month = nov,

doi = "10.1111/rssa.12955",

language = "English",

volume = "185",

pages = "S112--S130",

journal = "Journal of the Royal Statistical Society. Series A: Statistics in Society",

issn = "0964-1998",

publisher = "Oxford University Press",

number = "S1",

}

TY - JOUR

T1 - Estimation of reproduction numbers in real time

T2 - Conceptual and statistical challenges

AU - Pellis, Lorenzo

AU - Birrell, Paul J.

AU - Blake, Joshua

AU - Overton, Christopher E.

AU - Scarabel, Francesca

AU - Stage, Helena B.

AU - Brooks-Pollock, Ellen

AU - Danon, Leon

AU - Hall, Ian

AU - House, Thomas A.

AU - Keeling, Matt J.

AU - Read, Jonathan M.

AU - De Angelis, Daniela

AU - JUNIPER Consortium

N1 - Funding Information: information Alan Turing Institute, Alexander von Humboldt-Stiftung, Economic and Social Research Council, Engineering and Physical Sciences Research Council, Grant/Award Numbers: EP/N510129/1; EP/V027468/1; EP/V051555/1; Medical Research Council, Grant/Award Numbers: MC UU 00002/11; MC/PC/19067; MR/V028456/1; MR/V038613/1; National Institute for Health Research, National Institute for Health Research Health Protection Research Unit, Grant/Award Number: NIHR200877; Royal Society, Grant/Award Number: INF∖R2∖180067; Wellcome Trust, Grant/Award Number: 202562/Z/16/ZThe authors are very grateful to Phillippa Spencer and the Defence Science and Technology Laboratory (DSTL) data provision team for the relentless data management and provision throughout the pandemic, which has been essential for real-time reproduction number and growth rate estimates. Publisher Copyright: © 2022 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.

PY - 2022/11

Y1 - 2022/11

N2 - The reproduction number (Formula presented.) 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 (Formula presented.), 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 (Formula presented.) 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.

AB - The reproduction number (Formula presented.) 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 (Formula presented.), 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 (Formula presented.) 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.

KW - growth rate

KW - real-time estimation

KW - reproduction numbers

UR - http://www.scopus.com/inward/record.url?scp=85143537561&partnerID=8YFLogxK

U2 - 10.1111/rssa.12955

DO - 10.1111/rssa.12955

M3 - Article

AN - SCOPUS:85143537561

SN - 0964-1998

VL - 185

SP - S112-S130

JO - Journal of the Royal Statistical Society. Series A: Statistics in Society

JF - Journal of the Royal Statistical Society. Series A: Statistics in Society

IS - S1

ER -

Estimation of reproduction numbers in real time: Conceptual and statistical challenges

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this