Chadeau-Hyam, Marc, Wang, Haowei, Eales, Oliver, Haw, David, Bodinier, Barbara, Whitaker, Matthew, Walters, Caroline E, Ainslie, Kylie E C, Atchison, Christina, Fronterre, Claudio, Diggle, Peter J, Page, Andrew J, Trotter, Alexander J, Ashby, Deborah, Barclay, Wendy, Taylor, Graham, Cooke, Graham, Ward, Helen, Darzi, Ara, Riley, Steven, Donnelly, Christl A, Elliott, Paul, The COVID-19 Genomics UK (COG-UK) Consortium, , Bashton, Matthew, Smith, Darren, Young, Greg, Nelson, Andrew and McCann, Clare (2022) SARS-CoV-2 infection and vaccine effectiveness in England (REACT-1): a series of cross-sectional random community surveys. The Lancet Respiratory Medicine, 10 (4). pp. 355-366. ISSN 2213-2600
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Abstract
Background: England has experienced a third wave of the COVID-19 epidemic since the end of May, 2021, coinciding with the rapid spread of the delta (B.1.617.2) variant, despite high levels of vaccination among adults. Vaccination rates (single dose) in England are lower among children aged 16–17 years and 12–15 years, whose vaccination in England commenced in August and September, 2021, respectively. We aimed to analyse the underlying dynamics driving patterns in SARS-CoV-2 prevalence during September, 2021, in England. Methods: The REal-time Assessment of Community Transmission-1 (REACT-1) study, which commenced data collection in May, 2020, involves a series of random cross-sectional surveys in the general population of England aged 5 years and older. Using RT-PCR swab positivity data from 100 527 participants with valid throat and nose swabs in round 14 of REACT-1 (Sept 9–27, 2021), we estimated community-based prevalence of SARS-CoV-2 and vaccine effectiveness against infection by combining round 14 data with data from round 13 (June 24 to July 12, 2021; n=172 862). Findings: During September, 2021, we estimated a mean RT-PCR positivity rate of 0·83% (95% CrI 0·76–0·89), with a reproduction number (R) overall of 1·03 (95% CrI 0·94–1·14). Among the 475 (62·2%) of 764 sequenced positive swabs, all were of the delta variant; 22 (4·63%; 95% CI 3·07–6·91) included the Tyr145His mutation in the spike protein associated with the AY.4 sublineage, and there was one Glu484Lys mutation. Age, region, key worker status, and household size jointly contributed to the risk of swab positivity. The highest weighted prevalence was observed among children aged 5–12 years, at 2·32% (95% CrI 1·96–2·73) and those aged 13–17 years, at 2·55% (2·11–3·08). The SARS-CoV-2 epidemic grew in those aged 5–11 years, with an R of 1·42 (95% CrI 1·18–1·68), but declined in those aged 18–54 years, with an R of 0·81 (0·68–0·97). At ages 18–64 years, the adjusted vaccine effectiveness against infection was 62·8% (95% CI 49·3–72·7) after two doses compared to unvaccinated people, for all vaccines combined, 44·8% (22·5–60·7) for the ChAdOx1 nCov-19 (Oxford–AstraZeneca) vaccine, and 71·3% (56·6–81·0) for the BNT162b2 (Pfizer–BioNTech) vaccine. In individuals aged 18 years and older, the weighted prevalence of swab positivity was 0·35% (95% CrI 0·31–0·40) if the second dose was administered up to 3 months before their swab but 0·55% (0·50–0·61) for those who received their second dose 3–6 months before their swab, compared to 1·76% (1·60–1·95) among unvaccinated individuals. Interpretation: In September, 2021, at the start of the autumn school term in England, infections were increasing exponentially in children aged 5–17 years, at a time when vaccination rates were low in this age group. In adults, compared to those who received their second dose less than 3 months ago, the higher prevalence of swab positivity at 3–6 months following two doses of the COVID-19 vaccine suggests an increased risk of breakthrough infections during this period. The vaccination programme needs to reach children as well as unvaccinated and partially vaccinated adults to reduce SARS-CoV-2 transmission and associated disruptions to work and education. Funding: Department of Health and Social Care, England.
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| Additional Information: | Funding information: This study was funded by the Department of Health and Social Care in England. Sequencing was provided through funding from the COVID-19 Genomics UK (COG-UK) Consortium. MC-H and MW acknowledge support from the H2020-EXPANSE project (Horizon 2020 grant No 874627). MC-H and BB acknowledge support from Cancer Research UK, Population Research Committee Project grant ‘Mechanomics’ (grant number 22184 to MC-H). SR and CAD acknowledge support from the MRC Centre for Global Infectious Disease Analysis, National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU), Wellcome Trust (200861/Z/16/Z, 200187/Z/15/Z), and Centres for Disease Control and Prevention (US, U01CK0005-01-02). GC is supported by an NIHR Professorship. HW acknowledges support from an NIHR Senior Investigator Award and the Wellcome Trust (205456/Z/16/Z). PE is Director of the MRC Centre for Environment and Health (MR/L01341X/1, MR/S019669/1). PE acknowledges support from Health Data Research UK; the NIHR Imperial Biomedical Research Centre; NIHR HPRUs in Chemical and Radiation Threats and Hazards, and Environmental Exposures and Health; the British Heart Foundation Centre for Research Excellence at Imperial College London (RE/18/4/34215); and the UK Dementia Research Institute at Imperial College London (MC_PC_17114). We thank The Huo Family Foundation for their support of our work on COVID-19. We thank key collaborators on this work: Kelly Beaver, Sam Clemens, Gary Welch, Nicholas Gilby, Kelly Ward, Galini Pantelidou, and Kevin Pickering (Ipsos MORI); Gianluca Fontana, Sutha Satkunarajah, Didi Thompson, and Lenny Naar (Institute of Global Health Innovation at Imperial College London); Eric Johnson, Rob Elliott, and Graham Blakoe (School of Public Health, Imperial College London); North West London Pathology and Public Health England for help in calibration of the laboratory analyses; the Patient Experience Research Centre at Imperial College London and the REACT Public Advisory Panel; Thanh Le Viet, Nabil-Fareed Alikhan, and Catherine Ludden (Quadram Institute, Norwich, UK); NHS Digital for access to the NHS register; the Department of Health and Social Care for logistic support; and the COVID-19 Taskforce of the Royal Statistical Society (UK) for helpful comments. SR acknowledges helpful discussion with attendees of meetings of the UK Government Scientific Pandemic Influenza – Modelling (SPI-M) committee. The Quadram authors gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC); their research was funded by the BBSRC Institute Strategic Programme Microbes in the Food Chain BB/R012504/1 and its constituent project BBS/E/F/000PR10352. We thank members of COG-UK for their contributions to generating the genomic data used in this study. COG-UK is supported by funding from the Medical Research Council (MRC), part of UK Research & Innovation (UKRI), NIHR, and Genome Research, operating as the Wellcome Sanger Institute. Funding Information: This study was funded by the Department of Health and Social Care in England. Sequencing was provided through funding from the COVID-19 Genomics UK (COG-UK) Consortium. MC-H and MW acknowledge support from the H2020-EXPANSE project (Horizon 2020 grant No 874627). MC-H and BB acknowledge support from Cancer Research UK, Population Research Committee Project grant ?Mechanomics? (grant number 22184 to MC-H). SR and CAD acknowledge support from the MRC Centre for Global Infectious Disease Analysis, National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU), Wellcome Trust (200861/Z/16/Z, 200187/Z/15/Z), and Centres for Disease Control and Prevention (US, U01CK0005-01-02). GC is supported by an NIHR Professorship. HW acknowledges support from an NIHR Senior Investigator Award and the Wellcome Trust (205456/Z/16/Z). PE is Director of the MRC Centre for Environment and Health (MR/L01341X/1, MR/S019669/1). PE acknowledges support from Health Data Research UK; the NIHR Imperial Biomedical Research Centre; NIHR HPRUs in Chemical and Radiation Threats and Hazards, and Environmental Exposures and Health; the British Heart Foundation Centre for Research Excellence at Imperial College London (RE/18/4/34215); and the UK Dementia Research Institute at Imperial College London (MC_PC_17114). We thank The Huo Family Foundation for their support of our work on COVID-19. We thank key collaborators on this work: Kelly Beaver, Sam Clemens, Gary Welch, Nicholas Gilby, Kelly Ward, Galini Pantelidou, and Kevin Pickering (Ipsos MORI); Gianluca Fontana, Sutha Satkunarajah, Didi Thompson, and Lenny Naar (Institute of Global Health Innovation at Imperial College London); Eric Johnson, Rob Elliott, and Graham Blakoe (School of Public Health, Imperial College London); North West London Pathology and Public Health England for help in calibration of the laboratory analyses; the Patient Experience Research Centre at Imperial College London and the REACT Public Advisory Panel; Thanh Le Viet, Nabil-Fareed Alikhan, and Catherine Ludden (Quadram Institute, Norwich, UK); NHS Digital for access to the NHS register; the Department of Health and Social Care for logistic support; and the COVID-19 Taskforce of the Royal Statistical Society (UK) for helpful comments. SR acknowledges helpful discussion with attendees of meetings of the UK Government Scientific Pandemic Influenza ? Modelling (SPI-M) committee. The Quadram authors gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC); their research was funded by the BBSRC Institute Strategic Programme Microbes in the Food Chain BB/R012504/1 and its constituent project BBS/E/F/000PR10352. We thank members of COG-UK for their contributions to generating the genomic data used in this study. COG-UK is supported by funding from the Medical Research Council (MRC), part of UK Research & Innovation (UKRI), NIHR, and Genome Research, operating as the Wellcome Sanger Institute. Matthew Bashton, Andrew Nelson, Darren Smith, Greg Young and Clare McCann are members of the COVID-19 Genomics UK consortium. |
| Subjects: | A400 Clinical Dentistry B100 Anatomy, Physiology and Pathology B900 Others in Subjects allied to Medicine |
| Department: | Faculties > Health and Life Sciences > Applied Sciences |
| Depositing User: | Elena Carlaw |
| Date Deposited: | 22 Jul 2022 14:48 |
| Last Modified: | 22 Jul 2022 15:00 |
| URI: | http://nrl.northumbria.ac.uk/id/eprint/49600 |
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