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Monitoring sociodemographic inequality in COVID-19 vaccination uptake in England: a national linked data study
  1. Ted Dolby1,
  2. Katie Finning1,
  3. Allan Baker2,
  4. Leigh Fowler-Dowd2,
  5. Kamlesh Khunti3,4,5,
  6. Cameron Razieh1,3,5,
  7. Thomas Yates3,5,
  8. Vahe Nafilyan1,6
  1. 1 Health Analysis and Life Events division, Office for National Statistics, Newport, UK
  2. 2 Population Health Analysis Team, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK
  3. 3 NIHR Leicester Biomedical Research Centre, Leicester, UK
  4. 4 University Hospitals of Leicester NHS Trust, Leicester, UK
  5. 5 Diabetes Research Centre, University of Leicester, Leicester, UK
  6. 6 London School of Hygiene & Tropical Medicine, London, UK
  1. Correspondence to Dr Katie Finning, Office for National Statistics, Newport, Newport, UK; katie.finning{at}ons.gov.uk

Abstract

Background The UK began an ambitious COVID-19 vaccination programme on 8 December 2020. This study describes variation in vaccination uptake by sociodemographic characteristics between December 2020 and August 2021.

Methods Using population-level administrative records linked to the 2011 Census, we estimated monthly first dose vaccination rates by age group and sociodemographic characteristics among adults aged 18 years or over in England. We also present a tool to display the results interactively.

Results Our sample included 35 223 466 adults. A lower percentage of males than females were vaccinated in the young and middle age groups (18–59 years) but not in the older age groups. Vaccination rates were highest among individuals of White British and Indian ethnic backgrounds and lowest among Black Africans (aged ≥80 years) and Black Caribbeans (18–79 years). Differences by ethnic group emerged as soon as vaccination roll-out commenced and widened over time. Vaccination rates were also lower among individuals who identified as Muslim, lived in more deprived areas, reported having a disability, did not speak English as their main language, lived in rented housing, belonged to a lower socioeconomic group, and had fewer qualifications.

Conclusion We found inequalities in COVID-19 vaccination uptake rates by sex, ethnicity, religion, area deprivation, disability status, English language proficiency, socioeconomic position and educational attainment, but some of these differences varied by age group. Research is urgently needed to understand why these inequalities exist and how they can be addressed.

  • COVID-19
  • VACCINATION
  • Health inequalities

Data availability statement

Data are available in a public, open access repository. The data on vaccination rates by sociodemographic characteristics used in this paper are publicly available via the COVID-19 Health Inequalities Monitoring for England (CHIME) tool (https://analytics.phe.gov.uk/apps/chime/) and are readily available for reuse.

This article is made freely available for personal use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

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Data availability statement

Data are available in a public, open access repository. The data on vaccination rates by sociodemographic characteristics used in this paper are publicly available via the COVID-19 Health Inequalities Monitoring for England (CHIME) tool (https://analytics.phe.gov.uk/apps/chime/) and are readily available for reuse.

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Footnotes

  • Twitter @katiefinning

  • TD and KF contributed equally.

  • Contributors Study conceptualisation was led by VN, TD and KF. VN, TD, KF, AB and LD contributed to the development of the research question, study design, with development of statistical aspects led by TD and VN. TD and VN were involved in data specification, curation and collection. TD, KF and VN conducted and checked the statistical analyses. AB and LD developed the tool to visualise the results. All authors contributed to the interpretation of the results. KF and VN wrote the first draft of the paper. TD, TY, CR, KK, AB contributed to the critical revision of the manuscript for important intellectual content. All authors approved the final version of the manuscript. VN had full access to all data in the study and takes responsibility of the integrity of the data and the accuracy of the data analysis and is therefore the guarantor of the study. The lead authors (TD and KF) affirm that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

  • Funding This research was funded by ONS and PHE. TY, KK and CR are supported by a grant from the UKRI (MRC)-DHSC (NIHR) COVID-19 Rapid Response Rolling Call (MR/V020536/1) and from HDR-UK (HDRUK2020.138).

  • Disclaimer The funding source played no part in the interpretation of the results.

  • Competing interests KK is Chair of the Ethnicity Subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and Member of SAGE.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.