Real-time nowcasting and forecasting of COVID-19 dynamics in England: The first wave

Paul Birrell; Joshua Blake; Edwin Van Leeuwen; Robert Gent; Daniela De Angelis

doi:10.1098/rstb.2020.0279

Real-time nowcasting and forecasting of COVID-19 dynamics in England: The first wave

Paul Birrell
, Joshua Blake
, Edwin Van Leeuwen
, Robert Gent
, Daniela De Angelis^*

^*Corresponding author for this work

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

67 Citations (Scopus)

158 Downloads (Pure)

Abstract

England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77-84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9-1.4%) overall but 17% (14-22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Original language	English
Article number	20200279
Number of pages	9
Journal	Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Volume	376
Issue number	1829
Early online date	31 May 2021
DOIs	https://doi.org/10.1098/rstb.2020.0279
Publication status	Published - 19 Jul 2021

Bibliographical note

Funding Information: This work was supported by the Medical Research Council (unit programme no. MC UU 00002/11) in partnership with Public Health England. In addition, J.B. received support by the EPSRC (EP/R01856/1). Prior to the pandemic, this project was developed under a grant from the National Institute for Health Research (HTA Project: 11/46/03). We gratefully acknowledge the access to the data from the United Kingdom Time Use Survey through the UK Data Service (http://doi.org/10.5255/UKDA-SN-8128-1).

Open Access: Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

Publishers Copyright: © 2021 The Authors.

Citation: Birrell Paul, Blake Joshua, van Leeuwen Edwin, Gent Nick and De Angelis Daniela 2021Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wavePhil. Trans. R. Soc. B3762020027920200279

DOI: http://doi.org/10.1098/rstb.2020.0279

Keywords

Bayesian
COVID-19
dynamics
forecasting
nowcasting
real-time

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Birrell2021Real-TimeNowcastingAndForecastingOfCOVID-19Phil.Trans.R.Soc.BFinal published version, 816 KBLicence: CC BY

Cite this

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title = "Real-time nowcasting and forecasting of COVID-19 dynamics in England: The first wave",

abstract = "England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75\%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81\% (95\% credible interval: 77-84\%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5\% in two regions, South West and London. By this date, an estimated 8\% of the population had been infected, with a higher proportion in London (17\%). The infection-to-fatality ratio is 1.1\% (0.9-1.4\%) overall but 17\% (14-22\%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.",

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note = "Funding Information: This work was supported by the Medical Research Council (unit programme no. MC UU 00002/11) in partnership with Public Health England. In addition, J.B. received support by the EPSRC (EP/R01856/1). Prior to the pandemic, this project was developed under a grant from the National Institute for Health Research (HTA Project: 11/46/03). We gratefully acknowledge the access to the data from the United Kingdom Time Use Survey through the UK Data Service (http://doi.org/10.5255/UKDA-SN-8128-1). Open Access: Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Publishers Copyright: {\textcopyright} 2021 The Authors. Citation: Birrell Paul, Blake Joshua, van Leeuwen Edwin, Gent Nick and De Angelis Daniela 2021Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wavePhil. Trans. R. Soc. B3762020027920200279 DOI: http://doi.org/10.1098/rstb.2020.0279",

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N1 - Funding Information: This work was supported by the Medical Research Council (unit programme no. MC UU 00002/11) in partnership with Public Health England. In addition, J.B. received support by the EPSRC (EP/R01856/1). Prior to the pandemic, this project was developed under a grant from the National Institute for Health Research (HTA Project: 11/46/03). We gratefully acknowledge the access to the data from the United Kingdom Time Use Survey through the UK Data Service (http://doi.org/10.5255/UKDA-SN-8128-1). Open Access: Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Publishers Copyright: © 2021 The Authors. Citation: Birrell Paul, Blake Joshua, van Leeuwen Edwin, Gent Nick and De Angelis Daniela 2021Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wavePhil. Trans. R. Soc. B3762020027920200279 DOI: http://doi.org/10.1098/rstb.2020.0279

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N2 - England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77-84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9-1.4%) overall but 17% (14-22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

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JO - Philosophical transactions of the Royal Society of London. Series B, Biological sciences

JF - Philosophical transactions of the Royal Society of London. Series B, Biological sciences

IS - 1829

M1 - 20200279

ER -

Real-time nowcasting and forecasting of COVID-19 dynamics in England: The first wave

Abstract

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Keywords

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