@article{e87a11a486ad4568ba67be52f5d0f0be,
title = "Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data",
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.",
keywords = "CoMix, COVID-19, Reproduction number, SARS-CoV-2, School closure, Social contacts",
author = "Munday, {James D.} and Jarvis, {Christopher I.} and Amy Gimma and Wong, {Kerry L.M.} and {van Zandvoort}, Kevin and {CMMID COVID-19 Working Group} and Yang Liu and Joel Hellewell and Davies, {Nicholas G.} and Villabona-Arenas, {C. Julian} and Eggo, {Rosalind M.} and Akira Endo and Bosse, {Nikos I.} and Gibbs, {Hamish P.} and Pearson, {Carl A.B.} and Sun, {Fiona Yueqian} and Mark Jit and Kathleen O{\textquoteright}Reilly and Yalda Jafari and Atkins, {Katherine E.} and Waterlow, {Naomi R.} and Alicia Rosello and Chan, {Yung Wai Desmond} and Foss, {Anna M.} and Quilty, {Billy J.} and Russell, {Timothy W.} and Stefan Flasche and Procter, {Simon R.} and William Waites and Barnard, {Rosanna C.} and Kucharski, {Adam J.} and Thibaut Jombart and Graham Medley and Rachel Lowe and Fabienne Krauer and Tully, {Damien C.} and Kiesha Prem and Jiayao Lei and Oliver Brady and Sandmann, {Frank G.} and Meakin, {Sophie R.} and Kaja Abbas and Knight, {Gwenan M.} and Matthew Quaife and Mihaly Koltai and Sam Abbott and Samuel Clifford and Sebastian Funk and Edmunds, {W. John}",
note = "Funding Information: 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{\textquoteright}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 {\textquoteleft}RECAP{\textquoteright} 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). Funding Information: CoMix is funded by the EU Horizon 2020 Research and Innovations Programme - project EpiPose (Epidemic Intelligence to Minimize COVID-19{\textquoteright}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). Funding Information: 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{\textquoteright}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 {\textquoteleft}RECAP{\textquoteright} 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). Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = sep,
day = "10",
doi = "10.1186/s12916-021-02107-0",
language = "English",
volume = "19",
journal = "BMC Medicine",
issn = "1741-7015",
publisher = "BioMed Central",
number = "1",
}