Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

CMMID COVID-19 Working Group, James D. Munday*, Christopher I. Jarvis, Amy Gimma, Kerry L.M. Wong, Kevin van Zandvoort, Yang Liu, Joel Hellewell, Nicholas G. Davies, C. Julian Villabona-Arenas, Rosalind M. Eggo, Akira Endo, Nikos I. Bosse, Hamish P. Gibbs, Carl A.B. Pearson, Fiona Yueqian Sun, Mark Jit, Kathleen O’Reilly, Yalda Jafari, Katherine E. AtkinsNaomi R. Waterlow, Alicia Rosello, Yung Wai Desmond Chan, Anna M. Foss, Billy J. Quilty, Timothy W. Russell, Stefan Flasche, Simon R. Procter, William Waites, Rosanna C. Barnard, Adam J. Kucharski, Thibaut Jombart, Graham Medley, Rachel Lowe, Fabienne Krauer, Damien C. Tully, Kiesha Prem, Jiayao Lei, Oliver Brady, Frank G. Sandmann, Sophie R. Meakin, Kaja Abbas, Gwenan M. Knight, Matthew Quaife, Mihaly Koltai, Sam Abbott, Samuel Clifford, Sebastian Funk, W. John Edmunds

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Background: Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods: We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results: Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion: Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.

Original languageEnglish
Article number233
Number of pages13
JournalBMC Medicine
Volume19
Issue number1
Early online date10 Sept 2021
DOIs
Publication statusPublished - Dec 2021

Funding

The following funding sources are acknowledged as providing funding for the named authors. Elrha R2HC/UK FCDO/Wellcome Trust/This research was partly funded by the National Institute for Health Research (NIHR) using UK Aid from the UK government to support global health research. The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care (KvZ). This project has received funding from the European Union’s Horizon 2020 research and innovation programme - project EpiPose (101003688: AG, WJE). FCDO/Wellcome Trust (Epidemic Preparedness Coronavirus Research Programme 221303/Z/20/Z: KvZ). This research was partly funded by the Global Challenges Research Fund (GCRF) project ‘RECAP’ managed through RCUK and ESRC (ES/P010873/1: CIJ). NIHR (PR-OD-1017-20002: WJE). UK MRC (MC_PC_19065 - Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: WJE). Wellcome Trust (210758/Z/18/Z: JDM, SFunk). Department of Health and Social Care School Infection Study (PHSEZU7510) (JDM, WJE). No funding (KW). CoMix is funded by the EU Horizon 2020 Research and Innovations Programme - project EpiPose (Epidemic Intelligence to Minimize COVID-19’s Public Health, Societal and Economical Impact, No. 101003688) and by the Medical Research Council (Understanding the dynamics and drivers of the COVID-2019 epidemic using real-time outbreak analytics MC_PC 19065). The following funding sources are acknowledged as providing funding for the working group authors. BBSRC LIDP (BB/M009513/1: DS). This research was partly funded by the Bill & Melinda Gates Foundation (INV-001754: MQ; INV-003174: KP, MJ, YL; INV-016832: SRP; NTD Modelling Consortium OPP1184344: CABP, GFM; OPP1139859: BJQ; OPP1183986: ESN; OPP1191821: MA); BMGF (INV-016832; OPP1157270: KA); EDCTP2 (RIA2020EF-2983-CSIGN: HPG); and ERC Starting Grant (#757699: MQ). This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme - project EpiPose (101003688: KP, MJ, PK, RCB, YL) and FCDO/Wellcome Trust (Epidemic Preparedness Coronavirus Research Programme 221303/Z/20/Z: CABP). This research was partly funded by the Global Challenges Research Fund (GCRF) project ‘RECAP’ managed through RCUK and ESRC (ES/P010873/1: TJ), HDR UK (MR/S003975/1: RME) and HPRU (this research was partly funded by the National Institute for Health Research (NIHR) using UK Aid from the UK government to support global health research. The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care200908: NIB), MRC (MR/N013638/1: NRW), Nakajima Foundation (AE), NIHR (16/136/46: BJQ; 16/137/109: BJQ, FYS, MJ, YL; Health Protection Research Unit for Modelling Methodology HPRU-2012-10096: TJ; NIHR200908: AJK, RME; NIHR200929: FGS, MJ, NGD; PR-OD-1017-20002: AR), Royal Society (Dorothy Hodgkin Fellowship: RL; RP\EA\180004: PK), UK DHSC/UK Aid/NIHR (PR-OD-1017-20001: HPG) and UK MRC (MC_PC_19065 - Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: NGD, RME, SC, TJ, YL; MR/P014658/1: GMK). The authors of this research received funding from the UK Public Health Rapid Support Team funded by the United Kingdom Department of Health and Social Care (TJ), UKRI Research England (NGD) and Wellcome Trust (206250/Z/17/Z: AJK, TWR; 206471/Z/17/Z: OJB; 208812/Z/17/Z: SC, SFlasche; 210758/Z/18/Z: JH, KS, SA, SRM). No funding (AMF, AS, CJVA, DCT, JW, KEA, YWDC).

Keywords

  • CoMix
  • COVID-19
  • reproduction number
  • SARS-CoV-2
  • school closure
  • social contacts

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