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Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England

Chen, H; Cao, Y; Feng, L; Zhao, Q; Torres, JRV; (2023) Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England. BMC public health , 23 (1) , Article 895. 10.1186/s12889-023-15801-w. Green open access

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Abstract

BACKGROUND: Mass vaccination has been a key strategy in effectively containing global COVID-19 pandemic that posed unprecedented social and economic challenges to many countries. However, vaccination rates vary across space and socio-economic factors, and are likely to depend on the accessibility to vaccination services, which is under-researched in literature. This study aims to empirically identify the spatially heterogeneous relationship between COVID-19 vaccination rates and socio-economic factors in England. METHODS: We investigated the percentage of over-18 fully vaccinated people at the small-area level across England up to 18 November 2021. We used multiscale geographically weighted regression (MGWR) to model the spatially heterogeneous relationship between vaccination rates and socio-economic determinants, including ethnic, age, economic, and accessibility factors. RESULTS: This study indicates that the selected MGWR model can explain 83.2% of the total variance of vaccination rates. The variables exhibiting a positive association with vaccination rates in most areas include proportion of population over 40, car ownership, average household income, and spatial accessibility to vaccination. In contrast, population under 40, less deprived population, and black or mixed ethnicity are negatively associated with the vaccination rates. CONCLUSIONS: Our findings indicate the importance of improving the spatial accessibility to vaccinations in developing regions and among specific population groups in order to promote COVID-19 vaccination.

Type: Article
Title: Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/s12889-023-15801-w
Publisher version: https://doi.org/10.1186/s12889-023-15801-w
Language: English
Additional information: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Keywords: COVID-19 vaccination, England, MGWR, Socio-economic factors, Spatial accessibility, Humans, COVID-19 Vaccines, Pandemics, COVID-19, Vaccination, England
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: https://discovery.ucl.ac.uk/id/eprint/10170957
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