How COVID-19 vaccination in England varied by geography, demography, deprivation and registry: Bayesian ecological modelling

COVID-19 vaccines were freely available in England through the NHS with initial rollout from late 2020, but uptake was highly variable by locality. What explains this variation? Middle Super Output Area level data for the Vaccine Registry (VR), 1st and 2nd Primaries (P1,P2) and Booster / 3rd Injection (B3I) was obtained from the COVID-19 Dashboard. Covariate sources included Census 2021, the Index of Multiple Deprivation (IMD), flu vaccination, the EU Referendum, military bases and prisons. VR divided by the Census population aged 12+ was designated VRx. Bayesian multilevel beta-binomial models including factors for lower tier local authority nested within region were fitted to the uptake. Outliers and the impacts of model terms and groups were estimated by Leave-one-out methods. Models converged and fit the data well with few outliers. P1 uptake was the key predictor of P2, which predicted B3I. Regional and Local Authority factors and interaction of IMD with VRx had strong impacts on P1. The area proportions of various ethnicities, younger age, international migration, voting to “Leave” the EU and declining census questions on religion or sexual orientation, were all negative predictors of P1 uptake. Amongst ethnicities the “Other White” group (including Eastern European nationalities) had the strongest impact. The centred “random effects” for London, South West, South East and East of England were credibly higher than for North West or North East. Differences between the ten highest and lowest nested local authority effects were credible and large. Percentage change in annual public health allocations to 2021-22 had a positive impact and partially explained regional and local effects. Modelling with the ratio of Vaccine Registry to eligible population improves predictive ability. Vaccination pandemic planning should prioritise the initial phase. Some possible proxies for distrust in government institutions, several ethnic minorities and in particular “Other White” communities and international migrants predict lower geographical uptake. Qualitative evidence is consistent with the need for active outreach to overcome language barriers. Local authority effects and outliers may reflect differences in NHS and public health strategy and capacity for relevant provision during the critical period of vaccination, its outset.

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Publication Details

Journal
BMC Public Health
Published
2026-09-09
DOI
https://doi.org/10.1186/s12889-026-29155-6
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

How COVID-19 vaccination in England varied by geography, demography, deprivation and registry: Bayesian ecological modelling

Greg Dropkin
BMC Public Health
COVID-19 epidemiological studies
article

How COVID-19 vaccination in England varied by geography, demography, deprivation and registry: Bayesian ecological modelling

Greg Dropkin
article en

Abstract

COVID-19 vaccines were freely available in England through the NHS with initial rollout from late 2020, but uptake was highly variable by locality. What explains this variation? Middle Super Output Area level data for the Vaccine Registry (VR), 1st and 2nd Primaries (P1,P2) and Booster / 3rd Injection (B3I) was obtained from the COVID-19 Dashboard. Covariate sources included Census 2021, the Index of Multiple Deprivation (IMD), flu vaccination, the EU Referendum, military bases and prisons. VR divided by the Census population aged 12+ was designated VRx. Bayesian multilevel beta-binomial models including factors for lower tier local authority nested within region were fitted to the uptake. Outliers and the impacts of model terms and groups were estimated by Leave-one-out methods. Models converged and fit the data well with few outliers. P1 uptake was the key predictor of P2, which predicted B3I. Regional and Local Authority factors and interaction of IMD with VRx had strong impacts on P1. The area proportions of various ethnicities, younger age, international migration, voting to “Leave” the EU and declining census questions on religion or sexual orientation, were all negative predictors of P1 uptake. Amongst ethnicities the “Other White” group (including Eastern European nationalities) had the strongest impact. The centred “random effects” for London, South West, South East and East of England were credibly higher than for North West or North East. Differences between the ten highest and lowest nested local authority effects were credible and large. Percentage change in annual public health allocations to 2021-22 had a positive impact and partially explained regional and local effects. Modelling with the ratio of Vaccine Registry to eligible population improves predictive ability. Vaccination pandemic planning should prioritise the initial phase. Some possible proxies for distrust in government institutions, several ethnic minorities and in particular “Other White” communities and international migrants predict lower geographical uptake. Qualitative evidence is consistent with the need for active outreach to overcome language barriers. Local authority effects and outliers may reflect differences in NHS and public health strategy and capacity for relevant provision during the critical period of vaccination, its outset.

BMC Public Health
Openalex Percentile: Top 12%
COVID-19 epidemiological studies
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How COVID-19 vaccination in England varied by geography, demography, deprivation and registry: Bayesian ecological modelling — Greg Dropkin · BMC Public Health (2026) | TGRS Research Map | TGRS