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COVID-19 booster vaccination uptake and infection breakthrough amongst health care workers in Wales: A national prospective cohort study
Stuart Bedston,
Emily Lowthian,
Christopher I Jarvis,
Ashley Akbari 
,
Jillian Beggs,
Declan Bradley,
Simon de Lusignan,
Rowena Griffiths,
Laura Herbert ,
Richard Hobbs,
Steven Kerr,
Jane Lyons,
Will Midgley ,
Rhiannon Owen ,
Jennifer K Quint,
Ruby Tsang,
Fatemeh Torabi ,
Aziz Sheikh,
Ronan Lyons
,
Jillian Beggs,
Declan Bradley,
Simon de Lusignan,
Rowena Griffiths,
Laura Herbert ,
Richard Hobbs,
Steven Kerr,
Jane Lyons,
Will Midgley ,
Rhiannon Owen ,
Jennifer K Quint,
Ruby Tsang,
Fatemeh Torabi ,
Aziz Sheikh,
Ronan Lyons
Vaccine, Volume: 41, Issue: 7, Pages: 1378 - 1389
Swansea University Authors:
Stuart Bedston, Emily Lowthian, Ashley Akbari , Rowena Griffiths, Laura Herbert , Jane Lyons, Will Midgley , Rhiannon Owen , Fatemeh Torabi , Ronan Lyons
DOI (Published version): 10.1016/j.vaccine.2023.01.023
Abstract
BackgroundFrom September 2021, Health Care Workers (HCWs) in Wales began receiving a COVID-19 booster vaccination. This is the first dose beyond the primary vaccination schedule. Given the emergence of new variants, vaccine waning vaccine, and increasing vaccination hesitancy, there is a need to und...
| Published in: | Vaccine |
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| ISSN: | 0264-410X |
| Published: |
Elsevier BV
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa62336 |
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| Abstract: |
BackgroundFrom September 2021, Health Care Workers (HCWs) in Wales began receiving a COVID-19 booster vaccination. This is the first dose beyond the primary vaccination schedule. Given the emergence of new variants, vaccine waning vaccine, and increasing vaccination hesitancy, there is a need to understand booster vaccine uptake and subsequent breakthrough in this high-risk population.MethodsWe conducted a prospective, national-scale, observational cohort study of HCWs in Wales using anonymised, linked data from the SAIL Databank. We analysed uptake of COVID-19 booster vaccinations from September 2021 to February 2022, with comparisons against uptake of the initial primary vaccination schedule. We also analysed booster breakthrough, in the form of PCR-confirmed SARS-Cov-2 infection, comparing to the second primary dose. Cox proportional hazard models were used to estimate associations for vaccination uptake and breakthrough regarding staff roles, socio-demographics, household composition, and other factors.ResultsWe derived a cohort of 73,030 HCWs living in Wales (78% female, 60% 18-49 years old). Uptake was quickest amongst HCWs aged 60+ years old (aHR 2.54, 95%CI 2.45—2.63), compared with those aged 18-29. Asian HCWs had quicker uptake (aHR 1.18, 95%CI 1.14—1.22), whilst Black HCWs had slower uptake (aHR 0.67, 95%CI 0.61—0.74), compared to white HCWs. HCWs residing in the least deprived areas were slightly quicker to have received a booster dose (aHR 1.12, 95%CI 1.09—1.16), compared with those in the most deprived areas. Strongest associations with breakthrough infections were found for those living with children (aHR 1.52, 95%CI 1.41—1.63), compared to two-adult only households. HCWs aged 60+ years old were less likely to get breakthrough infections, compared to those aged 18-29 (aHR 0.42, 95%CI 0.38—0.47).ConclusionVaccination uptake was consistently lower among black HCWs, as well as those from deprived areas. Whilst breakthrough infections were highest in households with children. |
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| Keywords: |
COVID-19; Health care workers; Booster; Vaccination; Uptake; Breakthrough |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
This research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20029). Data and Connectivity: COVID-19 Vaccines Pharmacovigilance National Core Study (DaC-VaP; MR/R008345/1) is a partnership between The University of Edinburgh, University of Oxford, University of Strathclyde, Queen’s University Belfast and Swansea University. The authors would like to acknowledge all other DaC-VaP collaborators not involved in these analyses but contributing to wider discussions and preceding outputs. We also need to acknowledge the support of BREATHE - The Health Data Research Hub for Respiratory Health [MC_PC_19004], which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK.
This work was supported by the Con-COV team funded by the Medical Research Council (grant number: MR/V028367/1). This work was supported by Health Data Research UK, which receives its funding from HDR UK Ltd (HDR-9006) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. This work was supported by the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). This work was supported by the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales. |
| Issue: |
7 |
| Start Page: |
1378 |
| End Page: |
1389 |