Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

Edward S. Knock; Lilith K. Whittles; John A. Lees; Pablo N. Perez-Guzman; Robert Verity; Richard G. FitzJohn; Katy A.M. Gaythorpe; Natsuko Imai; Wes Hinsley; Lucy C. Okell; Alicia Rosello; Nikolas Kantas; Caroline E. Walters; Sangeeta Bhatia; Oliver J. Watson; Charlie Whittaker; Lorenzo Cattarino; Adhiratha Boonyasiri; Bimandra A. Djaafara; Keith Fraser; Han Fu; Haowei Wang; Xiaoyue Xi; Christl A. Donnelly; Elita Jauneikaite; Daniel J. Laydon; Peter J. White; Azra C. Ghani; Neil M. Ferguson; Anne Cori; Marc Baguelin

doi:10.1126/scitranslmed.abg4262

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

Edward S. Knock, Lilith K. Whittles, John A. Lees, Pablo N. Perez-Guzman, Robert Verity, Richard G. FitzJohn, Katy A.M. Gaythorpe, Natsuko Imai, Wes Hinsley, Lucy C. Okell, Alicia Rosello, Nikolas Kantas, Caroline E. Walters, Sangeeta Bhatia, Oliver J. Watson, Charlie Whittaker, Lorenzo Cattarino, Adhiratha Boonyasiri, Bimandra A. Djaafara, Keith FraserHan Fu, Haowei Wang, Xiaoyue Xi, Christl A. Donnelly, Elita Jauneikaite, Daniel J. Laydon, Peter J. White, Azra C. Ghani, Neil M. Ferguson, Anne Cori, Marc Baguelin

Modelling Economics Unit

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63 Citations (Scopus)

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Abstract

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.

Original language	English
Article number	4262
Number of pages	11
Journal	Science Translational Medicine
Volume	13
Issue number	602
DOIs	https://doi.org/10.1126/scitranslmed.abg4262
Publication status	Published - 14 Jul 2021

Bibliographical note

Funder Information: This work was supported by the NIHR HPRU in Modelling and Health Economics—a partnership between PHE, Imperial College London, and LSHTM (to N.M.F., grant code NIHR200908)—and the NIHR HPRU in Emerging and Zoonotic Infections—a partnership between PHE, University of Liverpool, University of Oxford, and Liverpool School of Tropical Medicine (to C.A.D., grant code NIHR200907). We acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (to N.M.F., reference MR/R015600/1), jointly funded by the U.K. Medical
Research Council (MRC) and the U.K. Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union

Open Access: Distributed under a Creative Commons Attribution License 4.0 (CC BY).

Publisher Copyright: Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Citation: Knock, Edward S., et al. "Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England." Science Translational Medicine (2021).

DOI: 10.1126/scitranslmed.abg4262

Keywords

NONPHARMACEUTICAL INTERVENTIONS
NURSING-HOMES
COVID-19
TRANSMISSION
DEATHS
OUTBREAKS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Knock, E. S., Whittles, L. K., Lees, J. A., Perez-Guzman, P. N., Verity, R., FitzJohn, R. G., Gaythorpe, K. A. M., Imai, N., Hinsley, W., Okell, L. C., Rosello, A., Kantas, N., Walters, C. E., Bhatia, S., Watson, O. J., Whittaker, C., Cattarino, L., Boonyasiri, A., Djaafara, B. A., ... Baguelin, M. (2021). Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England. Science Translational Medicine, 13(602), Article 4262. https://doi.org/10.1126/scitranslmed.abg4262

@article{05cd9df6f9ee444784919c6ae3de0bc8,

title = "Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England",

abstract = "We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.",

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author = "Knock, {Edward S.} and Whittles, {Lilith K.} and Lees, {John A.} and Perez-Guzman, {Pablo N.} and Robert Verity and FitzJohn, {Richard G.} and Gaythorpe, {Katy A.M.} and Natsuko Imai and Wes Hinsley and Okell, {Lucy C.} and Alicia Rosello and Nikolas Kantas and Walters, {Caroline E.} and Sangeeta Bhatia and Watson, {Oliver J.} and Charlie Whittaker and Lorenzo Cattarino and Adhiratha Boonyasiri and Djaafara, {Bimandra A.} and Keith Fraser and Han Fu and Haowei Wang and Xiaoyue Xi and Donnelly, {Christl A.} and Elita Jauneikaite and Laydon, {Daniel J.} and White, {Peter J.} and Ghani, {Azra C.} and Ferguson, {Neil M.} and Anne Cori and Marc Baguelin",

note = "Funder Information: This work was supported by the NIHR HPRU in Modelling and Health Economics—a partnership between PHE, Imperial College London, and LSHTM (to N.M.F., grant code NIHR200908)—and the NIHR HPRU in Emerging and Zoonotic Infections—a partnership between PHE, University of Liverpool, University of Oxford, and Liverpool School of Tropical Medicine (to C.A.D., grant code NIHR200907). We acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (to N.M.F., reference MR/R015600/1), jointly funded by the U.K. Medical Research Council (MRC) and the U.K. Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union Open Access: Distributed under a Creative Commons Attribution License 4.0 (CC BY). Publisher Copyright: Copyright {\textcopyright} 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Citation: Knock, Edward S., et al. {"}Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England.{"} Science Translational Medicine (2021). DOI: 10.1126/scitranslmed.abg4262",

year = "2021",

month = jul,

day = "14",

doi = "10.1126/scitranslmed.abg4262",

language = "English",

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journal = "Science Translational Medicine",

issn = "1946-6234",

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Knock, ES, Whittles, LK, Lees, JA, Perez-Guzman, PN, Verity, R, FitzJohn, RG, Gaythorpe, KAM, Imai, N, Hinsley, W, Okell, LC, Rosello, A, Kantas, N, Walters, CE, Bhatia, S, Watson, OJ, Whittaker, C, Cattarino, L, Boonyasiri, A, Djaafara, BA, Fraser, K, Fu, H, Wang, H, Xi, X, Donnelly, CA, Jauneikaite, E, Laydon, DJ, White, PJ, Ghani, AC, Ferguson, NM, Cori, A & Baguelin, M 2021, 'Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England', Science Translational Medicine, vol. 13, no. 602, 4262. https://doi.org/10.1126/scitranslmed.abg4262

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T1 - Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

AU - Knock, Edward S.

AU - Whittles, Lilith K.

AU - Lees, John A.

AU - Perez-Guzman, Pablo N.

AU - Verity, Robert

AU - FitzJohn, Richard G.

AU - Gaythorpe, Katy A.M.

AU - Imai, Natsuko

AU - Hinsley, Wes

AU - Okell, Lucy C.

AU - Rosello, Alicia

AU - Kantas, Nikolas

AU - Walters, Caroline E.

AU - Bhatia, Sangeeta

AU - Watson, Oliver J.

AU - Whittaker, Charlie

AU - Cattarino, Lorenzo

AU - Boonyasiri, Adhiratha

AU - Djaafara, Bimandra A.

AU - Fraser, Keith

AU - Fu, Han

AU - Wang, Haowei

AU - Xi, Xiaoyue

AU - Donnelly, Christl A.

AU - Jauneikaite, Elita

AU - Laydon, Daniel J.

AU - White, Peter J.

AU - Ghani, Azra C.

AU - Ferguson, Neil M.

AU - Cori, Anne

AU - Baguelin, Marc

N1 - Funder Information: This work was supported by the NIHR HPRU in Modelling and Health Economics—a partnership between PHE, Imperial College London, and LSHTM (to N.M.F., grant code NIHR200908)—and the NIHR HPRU in Emerging and Zoonotic Infections—a partnership between PHE, University of Liverpool, University of Oxford, and Liverpool School of Tropical Medicine (to C.A.D., grant code NIHR200907). We acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (to N.M.F., reference MR/R015600/1), jointly funded by the U.K. Medical Research Council (MRC) and the U.K. Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union Open Access: Distributed under a Creative Commons Attribution License 4.0 (CC BY). Publisher Copyright: Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Citation: Knock, Edward S., et al. "Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England." Science Translational Medicine (2021). DOI: 10.1126/scitranslmed.abg4262

PY - 2021/7/14

Y1 - 2021/7/14

N2 - We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.

AB - We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.

KW - NONPHARMACEUTICAL INTERVENTIONS

KW - NURSING-HOMES

KW - COVID-19

KW - TRANSMISSION

KW - DEATHS

KW - OUTBREAKS

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DO - 10.1126/scitranslmed.abg4262

M3 - Article

C2 - 34158411

AN - SCOPUS:85112125924

SN - 1946-6234

VL - 13

JO - Science Translational Medicine

JF - Science Translational Medicine

IS - 602

M1 - 4262

ER -

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

Abstract

Bibliographical note

Keywords

UN SDGs

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