@article{Chen_H-2023_136459,
title = {Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England},
author = {Chen, H. and Cao, Y. and Feng, L. and Zhao, Q. and Verduzco Torres, J.},
month = {may},
year = {2023},
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.},
volume = {23},
journal = {BMC Public Health},
publisher = {Springer Nature},
url = {https://doi.org/10.1186/s12889-023-15801-w},
}
