Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era

Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group; Rosanna C. Barnard; Nicholas G. Davies; James D. Munday; Rachel Lowe; Gwenan M. Knight; Quentin J. Leclerc; Damien C. Tully; David Hodgson; Rachael Pung; Joel Hellewell; Mihaly Koltai; David Simons; Kaja Abbas; Adam J. Kucharski; Simon R. Procter; Frank G. Sandmann; Carl A.B. Pearson; Kiesha Prem; Alicia Showering; Sophie R. Meakin; Kathleen O’Reilly; Ciara V. McCarthy; Matthew Quaife; Kerry L.M. Wong; Yalda Jafari; Arminder K. Deol; Rein M.G.J. Houben; Charlie Diamond; Thibaut Jombart; C. Julian Villabona-Arenas; William Waites; Rosalind M. Eggo; Akira Endo; Hamish P. Gibbs; Petra Klepac; Jack Williams; Billy J. Quilty; Oliver Brady; Jon C. Emery; Katherine E. Atkins; Lloyd A.C. Chapman; Katharine Sherratt; Sam Abbott; Nikos I. Bosse; Paul Mee; Sebastian Funk; Jiayao Lei; Yang Liu; Stefan Flasche; James W. Rudge

doi:10.1038/s41467-022-32404-y

Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era

Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group, Rosanna C. Barnard^*, Nicholas G. Davies, James D. Munday, Rachel Lowe, Gwenan M. Knight, Quentin J. Leclerc, Damien C. Tully, David Hodgson, Rachael Pung, Joel Hellewell, Mihaly Koltai, David Simons, Kaja Abbas, Adam J. Kucharski, Simon R. Procter, Frank G. Sandmann, Carl A.B. Pearson, Kiesha Prem, Alicia ShoweringSophie R. Meakin, Kathleen O’Reilly, Ciara V. McCarthy, Matthew Quaife, Kerry L.M. Wong, Yalda Jafari, Arminder K. Deol, Rein M.G.J. Houben, Charlie Diamond, Thibaut Jombart, C. Julian Villabona-Arenas, William Waites, Rosalind M. Eggo, Akira Endo, Hamish P. Gibbs, Petra Klepac, Jack Williams, Billy J. Quilty, Oliver Brady, Jon C. Emery, Katherine E. Atkins, Lloyd A.C. Chapman, Katharine Sherratt, Sam Abbott, Nikos I. Bosse, Paul Mee, Sebastian Funk, Jiayao Lei, Yang Liu, Stefan Flasche, James W. Rudge

^*Corresponding author for this work

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

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Abstract

England has experienced a heavy burden of COVID-19, with multiple waves of SARS-CoV-2 transmission since early 2020 and high infection levels following the emergence and spread of Omicron variants since late 2021. In response to rising Omicron cases, booster vaccinations were accelerated and offered to all adults in England. Using a model fitted to more than 2 years of epidemiological data, we project potential dynamics of SARS-CoV-2 infections, hospital admissions and deaths in England to December 2022. We consider key uncertainties including future behavioural change and waning immunity and assess the effectiveness of booster vaccinations in mitigating SARS-CoV-2 disease burden between October 2021 and December 2022. If no new variants emerge, SARS-CoV-2 transmission is expected to decline, with low levels remaining in the coming months. The extent to which projected SARS-CoV-2 transmission resurges later in 2022 depends largely on assumptions around waning immunity and to some extent, behaviour, and seasonality.

Original language	English
Article number	4879
Number of pages	15
Journal	Nature Communications
Volume	13
Issue number	1
Early online date	19 Aug 2022
DOIs	https://doi.org/10.1038/s41467-022-32404-y
Publication status	Published - 31 Dec 2022
Externally published	Yes

Funding

The following funding sources are acknowledged as providing funding for the named authors. This project has received funding from the European Union’s Horizon 2020 research and innovation programme - project EpiPose (Grant agreement number 101003688: R.C.B., M.J., W.J.E.). This work reflects only the authors’ view. The European Commission is not responsible for any use that may be made of the information it contains. This project has also received funding from the UK Medical Research Council (MC_PC_19065: N.G.D., W.J.E.), was partly funded by the National Institute for Health and Care Research (NIHR) (Health Protection Research Unit in Immunisation NIHR200929: N.G.D., M.J.; Health Protection Research Unit in Modelling and Health Economics NIHR200908: M.J., W.J.E.; PR-OD-1017-20002: W.J.E.). Funding statements for CMMID COVID-19 working group members are listed in the Supplementary Information. The authors would like to thank Stephen J. Rivers, Lloyd A. C. Chapman and Ciara V. McCarthy for helpful discussions which have contributed towards completion of this work. The following funding sources are acknowledged as providing funding for the named authors. This project has received funding from the European Union’s Horizon 2020 research and innovation programme - project EpiPose (Grant agreement number 101003688: R.C.B., M.J., W.J.E.). This work reflects only the authors’ view. The European Commission is not responsible for any use that may be made of the information it contains. This project has also received funding from the UK Medical Research Council (MC_PC_19065: N.G.D., W.J.E.), was partly funded by the National Institute for Health and Care Research (NIHR) (Health Protection Research Unit in Immunisation NIHR200929: N.G.D., M.J.; Health Protection Research Unit in Modelling and Health Economics NIHR200908: M.J., W.J.E.; PR-OD-1017-20002: W.J.E.). Funding statements for CMMID COVID-19 working group members are listed in the Supplementary Information. The authors would like to thank Stephen J. Rivers, Lloyd A. C. Chapman and Ciara V. McCarthy for helpful discussions which have contributed towards completion of this work.

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Covid-19
modelling
medium-term dynamics
SARS-CoV-2 transmission
England
Omicron variant

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10.1038/s41467-022-32404-yLicence: CC BY 4.0

Barnard-etal-NC-2022-Modelling-the-medium-term-dynamics-of-SARS-CoV-2-transmission-in-England-in-the-Omicron-eraFinal published version, 1.52 MBLicence: CC BY 4.0

Cite this

Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group, Barnard, R. C., Davies, N. G., Munday, J. D., Lowe, R., Knight, G. M., Leclerc, Q. J., Tully, D. C., Hodgson, D., Pung, R., Hellewell, J., Koltai, M., Simons, D., Abbas, K., Kucharski, A. J., Procter, S. R., Sandmann, F. G., Pearson, C. A. B., Prem, K., ... Rudge, J. W. (2022). Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era. Nature Communications, 13(1), Article 4879. https://doi.org/10.1038/s41467-022-32404-y

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abstract = "England has experienced a heavy burden of COVID-19, with multiple waves of SARS-CoV-2 transmission since early 2020 and high infection levels following the emergence and spread of Omicron variants since late 2021. In response to rising Omicron cases, booster vaccinations were accelerated and offered to all adults in England. Using a model fitted to more than 2 years of epidemiological data, we project potential dynamics of SARS-CoV-2 infections, hospital admissions and deaths in England to December 2022. We consider key uncertainties including future behavioural change and waning immunity and assess the effectiveness of booster vaccinations in mitigating SARS-CoV-2 disease burden between October 2021 and December 2022. If no new variants emerge, SARS-CoV-2 transmission is expected to decline, with low levels remaining in the coming months. The extent to which projected SARS-CoV-2 transmission resurges later in 2022 depends largely on assumptions around waning immunity and to some extent, behaviour, and seasonality.",

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Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group, Barnard, RC, Davies, NG, Munday, JD, Lowe, R, Knight, GM, Leclerc, QJ, Tully, DC, Hodgson, D, Pung, R, Hellewell, J, Koltai, M, Simons, D, Abbas, K, Kucharski, AJ, Procter, SR, Sandmann, FG, Pearson, CAB, Prem, K, Showering, A, Meakin, SR, O’Reilly, K, McCarthy, CV, Quaife, M, Wong, KLM, Jafari, Y, Deol, AK, Houben, RMGJ, Diamond, C, Jombart, T, Villabona-Arenas, CJ, Waites, W, Eggo, RM, Endo, A, Gibbs, HP, Klepac, P, Williams, J, Quilty, BJ, Brady, O, Emery, JC, Atkins, KE, Chapman, LAC, Sherratt, K, Abbott, S, Bosse, NI, Mee, P, Funk, S, Lei, J, Liu, Y, Flasche, S & Rudge, JW 2022, 'Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era', Nature Communications, vol. 13, no. 1, 4879. https://doi.org/10.1038/s41467-022-32404-y

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AU - Deol, Arminder K.

AU - Houben, Rein M.G.J.

AU - Diamond, Charlie

AU - Jombart, Thibaut

AU - Villabona-Arenas, C. Julian

AU - Waites, William

AU - Eggo, Rosalind M.

AU - Endo, Akira

AU - Gibbs, Hamish P.

AU - Klepac, Petra

AU - Williams, Jack

AU - Quilty, Billy J.

AU - Brady, Oliver

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AU - Atkins, Katherine E.

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AU - Abbott, Sam

AU - Bosse, Nikos I.

AU - Mee, Paul

AU - Funk, Sebastian

AU - Lei, Jiayao

AU - Liu, Yang

AU - Flasche, Stefan

AU - Rudge, James W.

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AB - England has experienced a heavy burden of COVID-19, with multiple waves of SARS-CoV-2 transmission since early 2020 and high infection levels following the emergence and spread of Omicron variants since late 2021. In response to rising Omicron cases, booster vaccinations were accelerated and offered to all adults in England. Using a model fitted to more than 2 years of epidemiological data, we project potential dynamics of SARS-CoV-2 infections, hospital admissions and deaths in England to December 2022. We consider key uncertainties including future behavioural change and waning immunity and assess the effectiveness of booster vaccinations in mitigating SARS-CoV-2 disease burden between October 2021 and December 2022. If no new variants emerge, SARS-CoV-2 transmission is expected to decline, with low levels remaining in the coming months. The extent to which projected SARS-CoV-2 transmission resurges later in 2022 depends largely on assumptions around waning immunity and to some extent, behaviour, and seasonality.

KW - Covid-19

KW - modelling

KW - medium-term dynamics

KW - SARS-CoV-2 transmission

KW - England

KW - Omicron variant

U2 - 10.1038/s41467-022-32404-y

DO - 10.1038/s41467-022-32404-y

M3 - Article

C2 - 35986002

AN - SCOPUS:85136912315

SN - 2041-1723

VL - 13

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 4879

ER -

Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era

Abstract

Funding

UN SDGs

Keywords

Access to Document

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