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

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.

Global and local drivers of Echinococcus multilocularis infection in the western Balkan region

“…For this reason, we applied the GWR model, which can analyse the local variations of relationships with a single bandwidth. This model relaxed the OLS model’s assumption that the relationship between the explanatory and the response variables is spatially homogeneous 24 . This model provided a better explanation rate for the variance, whereas it increased from 7.8 to 37.6%.…”

“…This model provided a better explanation rate for the variance, whereas it increased from 7.8 to 37.6%. The GWR model assumes that all independent variables influence the dependent variable within the same spatial scale, thus ignoring local multicollinearity and causing overfitting and less reliable parameter estimates 24 .…”

Public transport accessibility indicators to urban and regional services in Great Britain

“…Accessibility indicators aim to measure “the ease of reaching valued destinations” 1 . Public transport accessibility has been found to influence human behaviour and urban and regional processes such as unemployment rates 2 , mode choice 3 , property prices 4 , public health 5 , 6 , and social inequity 7 . Accessibility is key for evaluating and addressing equity objectives in transport planning, policy, and projects 8 .…”

“…The procedure can be aided by the process followed for this work, as it is similar to the one shown in the code for the services included. This is also applicable to examining other specific services such as the accessibility to vaccination sites, as the COVID-19 uptake rate has been shown to be associated with the level of accessibility 6 .…”

Investigating the impact of Socio-Demographic and Urban Built Environments on the Spatial Heterogeneity of Flu Vaccine Locations – A Case Study from New York City, United States

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