Abstract
Understanding how the effectiveness of coronavirus disease 2019 (COVID-19) vaccine changes over time and in response to new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is crucial to scheduling subsequent doses. In a previous study, Horne et al. (1) quantified vaccine effectiveness (VE) over 6 consecutive 4-week periods from 2 weeks to 26 weeks after the second dose. Waning of hazard ratios (HRs) when comparing vaccinated persons with unvaccinated persons was approximately log-linear over time and was consistent across COVID-19–related outcomes and risk-based subgroups. To investigate waning beyond 26 weeks and in the era of the Omicron variant, we extended follow-up to the earliest of 50 weeks after the second dose or March 31, 2022.
| Original language | English |
|---|---|
| Article number | kwad179 |
| Pages (from-to) | 227-231 |
| Number of pages | 5 |
| Journal | American Journal of Epidemiology |
| Volume | 193 |
| Issue number | 1 |
| Early online date | 1 Sept 2023 |
| DOIs | |
| Publication status | Published - 8 Jan 2024 |
Bibliographical note
Funding Information:A.M. is a member of the NHS Digital Professional Advisory Group (representing the Royal College of General Practitioners), advising on the use of general practice data for COVID-19–related research and planning; until September 2019, he was interim chief medical officer of NHS Digital. B.G. has received research funding from the Laura and John Arnold Foundation, the NIHR, the NIHR School of Primary Care Research, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organization, UKRI, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies Programme. He receives personal income from speaking and writing for lay audiences on the misuse of science; he is also a nonexecutive director of NHS Digital.
Funding Information:
This work was supported by UK Research and Innovation (UKRI) research councils (grants COV0076 and MR/V015737/1), the Longitudinal Health and Wellbeing strand of the National Core Studies Programme (grants MC_PC_20030 and MC_PC_20059), the National Institute for Health and Care Research (NIHR) Convalescence Study (grant COV-LT-0009), and Asthma UK. The OpenSAFELY data science platform is funded by the Wellcome Trust (grant 222097/Z/20/Z). The work of E.M.F.H. and J.A.C.S. was funded in part by NIHR grant 135073. R.H.K.’s work was funded by UKRI (Future Leaders Fellowship MR/S017968/1). T.M.P. was supported by the MRC Integrative Epidemiology Unit, which receives funding from the UKRI Medical Research Council and the University of Bristol (grants MC_UU_00011/1 and MC_UU_00011/3). E.J.W. received grants from the Medical Research Council (MRC). The work of E.P.K.P. was funded by UKRI (COVID-19 data analysis secondment MR/W021420/1). Y.W. was supported by a UKRI MRC Fellowship (fellowship MC/W021358/1) and received funding from a UKRI Engineering and Physical Sciences Research Council Impact Acceleration Account (grant EP/X525789/1). B.G.’s work on better use of data in health care more broadly is currently funded in part by the Bennett Foundation, the Wellcome Trust, the NIHR Oxford Biomedical Research Centre, the NIHR Applied Research Collaboration Oxford and Thames Valley, and the Mohn-Westlake Foundation; all Bennett Institute staff are supported by B.G.’s grants on this work. J.A.C.S. was additionally supported by the NIHR Bristol Biomedical Research Centre and by Health Data Research UK.
Funding Information:
This work was supported by UK Research and Innovation (UKRI) research councils (grants COV0076 and MR/V015737/1), the Longitudinal Health and Wellbeing strand of the National Core Studies Programme (grants MC_PC_20030 and MC_PC_20059), the National Institute for Health and Care Research (NIHR) Convalescence Study (grant COV-LT-0009), and Asthma UK. The OpenSAFELY data science platform is funded by the Wellcome Trust (grant 222097/Z/20/Z). The work of E.M.F.H. and J.A.C.S. was funded in part by NIHR grant 135073. R.H.K.'s work was funded by UKRI (Future Leaders Fellowship MR/S017968/1). T.M.P. was supported by the MRC Integrative Epidemiology Unit, which receives funding from the UKRI Medical Research Council and the University of Bristol (grants MC_UU_00011/1 and MC_UU_00011/3). E.J.W. received grants from the Medical Research Council (MRC). The work of E.P.K.P. was funded by UKRI (COVID-19 data analysis secondment MR/W021420/1). Y.W. was supported by a UKRI MRC Fellowship (fellowship MC/W021358/1) and received funding from a UKRI Engineering and Physical Sciences Research Council Impact Acceleration Account (grant EP/X525789/1). B.G.'s work on better use of data in health care more broadly is currently funded in part by the Bennett Foundation, the Wellcome Trust, the NIHR Oxford Biomedical Research Centre, the NIHR Applied Research Collaboration Oxford and Thames Valley, and the Mohn-Westlake Foundation; all Bennett Institute staff are supported by B.G.'s grants on this work. J.A.C.S. was additionally supported by the NIHR Bristol Biomedical Research Centre and by Health Data Research UK. All data were linked, stored, and analyzed securely within the OpenSAFELY platform (https://opensafely. org/). Data included pseudonymized information such as coded diagnoses, medications, and physiological parameters. No free-text data were included. Detailed pseudonymized patient data are potentially reidentifiable and therefore are not shared. Primary-care records managed by the general practitioner software provider, The Phoenix Partnership/EMIS (Egton Medical Information Systems, Leeds, United Kingdom), were linked to COVID-19 test results, hospital admissions, hospital deaths (COVID-19 only), and registered deaths through OpenSAFELY. Data management was performed using Python 3.8.10, with analysis carried out using R, version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria). All software code is shared openly for review and reuse under the MIT License (https://github.com/opensafely/waning-ve-2dose-1year). We are very grateful for all of the support received from the Phoenix Partnership technical operations team throughout this work, and for the generous assistance provided by the information governance and database teams of the National Health Service (NHS) (NHS England and the NHS England Transformation Directorate). A preprint of this letter is available in medRχiv (https://www.medrxiv.org/content/10.1101/2023.01.04.22283762v1). The views expressed in this letter are those of the authors and not necessarily those of the NIHR, NHS England, the UK Health Security Agency, or the UK Department of Health and Social Care. The funders played no role in the consideration of the study design; in the collection, analysis, and interpretation of the data; in the writing of the report; or in the decision to submit the article for publication. A.M. is a member of the NHS Digital Professional Advisory Group (representing the Royal College of General Practitioners), advising on the use of general practice data for COVID-19-related research and planning; until September 2019, he was interim chief medical officer of NHS Digital. B.G. has received research funding from the Laura and John Arnold Foundation, the NIHR, the NIHR School of Primary Care Research, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organization, UKRI, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies Programme. He receives personal income from speaking and writing for lay audiences on the misuse of science; he is also a nonexecutive director of NHS Digital.
