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Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis
Vaccine, Volume: 41, Issue: 49, Pages: 7333 - 7341
Swansea University Authors: Rowena Bailey, Sudha Arumugam, Ashley Akbari , Rich Fry , Ronan Lyons
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DOI (Published version): 10.1016/j.vaccine.2023.10.066
Abstract
Vaccination has proven to be effective at preventing severe outcomes of COVID-19 infection, and uptake in the population has been high in Wales. However, there is a risk that high-level vaccination coverage statistics may mask hidden inequalities in under-served populations, many of whom may be at i...
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ISSN: | 0264-410X |
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Elsevier BV
2023
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However, there is a risk that high-level vaccination coverage statistics may mask hidden inequalities in under-served populations, many of whom may be at increased risk of severe outcomes of COVID-19 infection. The study population included 1,436,229 individuals aged 18 years and over, alive and residence in Wales as at 31st July 2022, and excluded immunosuppressed or care home residents. We compared people who had received one or more vaccinations to those with no vaccination using linked data from nine datasets within the Secure Anonymised Information Linkage (SAIL) databank. Multivariable analysis was undertaken to determine the impact of a range of sociodemographic characteristics on vaccination uptake, including ethnicity, country of birth, severe mental illness, homelessness and substance use. We found that overall uptake of first dose of COVID-19 vaccination was high in Wales (92.1 %), with the highest among those aged 80 years and over and females. Those aged under 40 years, household composition (aOR 0.38 95 %CI 0.35–0.41 for 10+ size household compared to two adult household) and being born outside the UK (aOR 0.44 95 %CI 0.43–0.46) had the strongest negative associations with vaccination uptake. This was followed by a history of substance misuse (aOR 0.45 95 %CI 0.44–0.46). Despite high-level population coverage in Wales, significant inequalities remain across several underserved groups. Factors associated with vaccination uptake should not be considered in isolation, to avoid drawing incorrect conclusions. Ensuring equitable access to vaccination is essential to protecting under-served groups from COVID-19 and further work needs to be done to address these gaps in coverage, with focus on tailored vaccination pathways and advocacy, using trusted partners and communities.</abstract><type>Journal Article</type><journal>Vaccine</journal><volume>41</volume><journalNumber>49</journalNumber><paginationStart>7333</paginationStart><paginationEnd>7341</paginationEnd><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0264-410X</issnPrint><issnElectronic/><keywords>Immunisation equity, COVID-19 vaccines, Vaccination, Immunisation, Socioeconomic factors, Under-served groups, Ethnic groups</keywords><publishedDay>1</publishedDay><publishedMonth>11</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-11-01</publishedDate><doi>10.1016/j.vaccine.2023.10.066</doi><url>http://dx.doi.org/10.1016/j.vaccine.2023.10.066</url><notes/><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported by the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales. 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. This work was supported by the ADR Wales programme of work. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant (ES/W012227/1).</funders><projectreference/><lastEdited>2023-12-04T14:51:38.9945806</lastEdited><Created>2023-11-05T19:49:10.2879037</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Health Data Science</level></path><authors><author><firstname>Gethin</firstname><surname>Jones</surname><order>1</order></author><author><firstname>Malorie</firstname><surname>Perry</surname><orcid>0000-0003-1397-5934</orcid><order>2</order></author><author><firstname>Rowena</firstname><surname>Bailey</surname><order>3</order></author><author><firstname>Sudha</firstname><surname>Arumugam</surname><order>4</order></author><author><firstname>Adrian</firstname><surname>Edwards</surname><orcid>0000-0002-6228-4446</orcid><order>5</order></author><author><firstname>Alex</firstname><surname>Lench</surname><order>6</order></author><author><firstname>Alison</firstname><surname>Cooper</surname><orcid>0000-0001-8660-6721</orcid><order>7</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>8</order></author><author><firstname>Brendan</firstname><surname>Collins</surname><orcid>0000-0002-3023-8189</orcid><order>9</order></author><author><firstname>Caroline</firstname><surname>Harris</surname><orcid>0000-0002-2778-3362</orcid><order>10</order></author><author><firstname>Gill</firstname><surname>Richardson</surname><orcid>0000-0001-8554-3271</orcid><order>11</order></author><author><firstname>Mai</firstname><surname>Barry</surname><orcid>0009-0003-6877-9823</orcid><order>12</order></author><author><firstname>Phillippa</firstname><surname>Harris</surname><orcid>0009-0001-2641-7889</orcid><order>13</order></author><author><firstname>Rich</firstname><surname>Fry</surname><orcid>0000-0002-7968-6679</orcid><order>14</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>15</order></author><author><firstname>Simon</firstname><surname>Cottrell</surname><order>16</order></author></authors><documents><document><filename>64916__29199__c12f65d7dad7405bbbb14d4b6f1ee5f9.pdf</filename><originalFilename>64916.VOR.pdf</originalFilename><uploaded>2023-12-04T14:44:12.7093062</uploaded><type>Output</type><contentLength>491046</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>Crown Copyright © 2023 Published by Elsevier Ltd. 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v2 64916 2023-11-05 Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis 455e2c1e6193448f6269b9e72acaf865 Rowena Bailey Rowena Bailey true false 6679f11a2f5dac900f1139aa791de2dd Sudha Arumugam Sudha Arumugam true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false d499b898d447b62c81b2c122598870e0 0000-0002-7968-6679 Rich Fry Rich Fry true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2023-11-05 HDAT Vaccination has proven to be effective at preventing severe outcomes of COVID-19 infection, and uptake in the population has been high in Wales. However, there is a risk that high-level vaccination coverage statistics may mask hidden inequalities in under-served populations, many of whom may be at increased risk of severe outcomes of COVID-19 infection. The study population included 1,436,229 individuals aged 18 years and over, alive and residence in Wales as at 31st July 2022, and excluded immunosuppressed or care home residents. We compared people who had received one or more vaccinations to those with no vaccination using linked data from nine datasets within the Secure Anonymised Information Linkage (SAIL) databank. Multivariable analysis was undertaken to determine the impact of a range of sociodemographic characteristics on vaccination uptake, including ethnicity, country of birth, severe mental illness, homelessness and substance use. We found that overall uptake of first dose of COVID-19 vaccination was high in Wales (92.1 %), with the highest among those aged 80 years and over and females. Those aged under 40 years, household composition (aOR 0.38 95 %CI 0.35–0.41 for 10+ size household compared to two adult household) and being born outside the UK (aOR 0.44 95 %CI 0.43–0.46) had the strongest negative associations with vaccination uptake. This was followed by a history of substance misuse (aOR 0.45 95 %CI 0.44–0.46). Despite high-level population coverage in Wales, significant inequalities remain across several underserved groups. Factors associated with vaccination uptake should not be considered in isolation, to avoid drawing incorrect conclusions. Ensuring equitable access to vaccination is essential to protecting under-served groups from COVID-19 and further work needs to be done to address these gaps in coverage, with focus on tailored vaccination pathways and advocacy, using trusted partners and communities. Journal Article Vaccine 41 49 7333 7341 Elsevier BV 0264-410X Immunisation equity, COVID-19 vaccines, Vaccination, Immunisation, Socioeconomic factors, Under-served groups, Ethnic groups 1 11 2023 2023-11-01 10.1016/j.vaccine.2023.10.066 http://dx.doi.org/10.1016/j.vaccine.2023.10.066 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University This work was supported by the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales. 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. This work was supported by the ADR Wales programme of work. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant (ES/W012227/1). 2023-12-04T14:51:38.9945806 2023-11-05T19:49:10.2879037 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Gethin Jones 1 Malorie Perry 0000-0003-1397-5934 2 Rowena Bailey 3 Sudha Arumugam 4 Adrian Edwards 0000-0002-6228-4446 5 Alex Lench 6 Alison Cooper 0000-0001-8660-6721 7 Ashley Akbari 0000-0003-0814-0801 8 Brendan Collins 0000-0002-3023-8189 9 Caroline Harris 0000-0002-2778-3362 10 Gill Richardson 0000-0001-8554-3271 11 Mai Barry 0009-0003-6877-9823 12 Phillippa Harris 0009-0001-2641-7889 13 Rich Fry 0000-0002-7968-6679 14 Ronan Lyons 0000-0001-5225-000X 15 Simon Cottrell 16 64916__29199__c12f65d7dad7405bbbb14d4b6f1ee5f9.pdf 64916.VOR.pdf 2023-12-04T14:44:12.7093062 Output 491046 application/pdf Version of Record true Crown Copyright © 2023 Published by Elsevier Ltd. Distributed under the terms of a Creative Commons Attribution 4.0 International License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/ |
title |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis |
spellingShingle |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis Rowena Bailey Sudha Arumugam Ashley Akbari Rich Fry Ronan Lyons |
title_short |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis |
title_full |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis |
title_fullStr |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis |
title_full_unstemmed |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis |
title_sort |
Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis |
author_id_str_mv |
455e2c1e6193448f6269b9e72acaf865 6679f11a2f5dac900f1139aa791de2dd aa1b025ec0243f708bb5eb0a93d6fb52 d499b898d447b62c81b2c122598870e0 83efcf2a9dfcf8b55586999d3d152ac6 |
author_id_fullname_str_mv |
455e2c1e6193448f6269b9e72acaf865_***_Rowena Bailey 6679f11a2f5dac900f1139aa791de2dd_***_Sudha Arumugam aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari d499b898d447b62c81b2c122598870e0_***_Rich Fry 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons |
author |
Rowena Bailey Sudha Arumugam Ashley Akbari Rich Fry Ronan Lyons |
author2 |
Gethin Jones Malorie Perry Rowena Bailey Sudha Arumugam Adrian Edwards Alex Lench Alison Cooper Ashley Akbari Brendan Collins Caroline Harris Gill Richardson Mai Barry Phillippa Harris Rich Fry Ronan Lyons Simon Cottrell |
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Vaccine |
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7333 |
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2023 |
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Swansea University |
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0264-410X |
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10.1016/j.vaccine.2023.10.066 |
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Elsevier BV |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science |
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http://dx.doi.org/10.1016/j.vaccine.2023.10.066 |
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description |
Vaccination has proven to be effective at preventing severe outcomes of COVID-19 infection, and uptake in the population has been high in Wales. However, there is a risk that high-level vaccination coverage statistics may mask hidden inequalities in under-served populations, many of whom may be at increased risk of severe outcomes of COVID-19 infection. The study population included 1,436,229 individuals aged 18 years and over, alive and residence in Wales as at 31st July 2022, and excluded immunosuppressed or care home residents. We compared people who had received one or more vaccinations to those with no vaccination using linked data from nine datasets within the Secure Anonymised Information Linkage (SAIL) databank. Multivariable analysis was undertaken to determine the impact of a range of sociodemographic characteristics on vaccination uptake, including ethnicity, country of birth, severe mental illness, homelessness and substance use. We found that overall uptake of first dose of COVID-19 vaccination was high in Wales (92.1 %), with the highest among those aged 80 years and over and females. Those aged under 40 years, household composition (aOR 0.38 95 %CI 0.35–0.41 for 10+ size household compared to two adult household) and being born outside the UK (aOR 0.44 95 %CI 0.43–0.46) had the strongest negative associations with vaccination uptake. This was followed by a history of substance misuse (aOR 0.45 95 %CI 0.44–0.46). Despite high-level population coverage in Wales, significant inequalities remain across several underserved groups. Factors associated with vaccination uptake should not be considered in isolation, to avoid drawing incorrect conclusions. Ensuring equitable access to vaccination is essential to protecting under-served groups from COVID-19 and further work needs to be done to address these gaps in coverage, with focus on tailored vaccination pathways and advocacy, using trusted partners and communities. |
published_date |
2023-11-01T14:51:40Z |
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11.037581 |