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

Chen, H., Cao, Y., Feng, L., Zhao, Q. and Verduzco-Torres, J. R. (2023) Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England. BMC Public Health, 23, 895. (doi: 10.1186/s12889-023-15801-w)

[img] Text
298518.pdf - Published Version
Available under License Creative Commons Attribution.



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.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Verduzco-Torres, Dr Jose Rafael and Zhao, Dr Qunshan
Creator Roles:
Zhao, Q.Conceptualization, Methodology, Validation, Writing – review and editing
Verduzco Torres, J. R.Software, Formal analysis, Writing – review and editing
Authors: Chen, H., Cao, Y., Feng, L., Zhao, Q., and Verduzco-Torres, J. R.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:BMC Public Health
Publisher:BioMed Central
ISSN (Online):1471-2458
Copyright Holders:Copyright © 2023 Crown
First Published:First published in BMC Public Health 23: 895
Publisher Policy:Reproduced under a Creative Commons license

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
190698Urban Big Data Research CentreNick BaileyEconomic and Social Research Council (ESRC)ES/L011921/1S&PS - Urban Big Data
304042UBDC Centre TransitionNick BaileyEconomic and Social Research Council (ESRC)ES/S007105/1S&PS - Administration