How does Vulnerability to COVID-19 Vary between Communities in England? Developing a Small Area Vulnerability Index (SAVI)
18 Pages Posted: 17 Jul 2020
Date Written: July 13, 2020
Background: During the initial wave of the COVID-19 epidemic in England, several population characteristics were associated with increased risk of mortality - including, age, ethnicity, income deprivation, care home residence and housing conditions. In order to target control measures and plan for future waves of the epidemic, public health agencies need to understand how these vulnerabilities are distributed across and clustered within communities. We therefore generated an empirically informed vulnerability index for small areas across England based on predictors of mortality risk observed during the first wave.
Methods: We performed a cross-sectional ecological analysis across 6,789 small areas in England. We assessed the association between COVID-19 mortality in each area and 5 vulnerability measures relating to ethnicity, poverty, prevalence of long-term health conditions, living in care homes and living in overcrowded housing, whilst accounting for the age profile of the population and the regional spread and duration of the epidemic. Estimates from multivariable Poisson regression models were used to derive a Small Area Vulnerability Index (SAVI) based on the association between these population vulnerability factors and COVID-19 mortality.
Results: Four vulnerability measures were independently associated with age-adjusted COVID-19 mortality. Each standard deviation increase in the proportion of the population (1) living in care homes, (2) admitted to hospital in the past 5 years for a long-term health condition, (3) from an ethnic minority background and (4) living in overcrowded housing was associated with a 28%, [IRR=1.28, 95%CI 1.26 to 1.31], 19% [IRR=1.19, 95%CI 1.15 to 1.22], 8% [IRR=1.08, 95%CI 1.03 to 1.13] and 11% [IRR=1.11, 95%CI 1.06 to 1.15] increase in age-adjusted COVID-19 mortality rate respectively. Vulnerability to COVID-19 was noticeably higher in the North West, West Midlands, and North East regions, with high levels of vulnerability clustered in some communities.
Conclusion: A second wave of the epidemic is likely to have more severe consequences for those communities identified as highly vulnerable by our index, with disproportionate affects in the North of England and the Midlands. Action is needed now to develop control measures to reduce vulnerability and increase resilience, in order to protect these communities and prevent further avoidable deaths, underpinned by proportionate allocation of resources.
Note: Funding: BB, TR and KD are supported by the National Institute for Health Research (NIHR) Applied Research Collaboration North West Coast (ARC NWC). BB, AA and DTR are supported by the NIHR School for Public Health Research. IB is supported by NIHR Senior Investigator award. DTR is funded by the MRC on a Clinician Scientist Fellowship (MR/P008577/1).
Conflict of Interest: BB, TR and KD are supported by the NIHR Applied Research Collaboration North West Coast; BB, AA and DTR are supported by the NIHR School for Public Health Research; DTR are funded by the Medical Research Council; IB is supported by NIHR Senior Investigator award; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
Ethical Approval: Ethics committee approval was not required for this study which analysed publicly available datasets (https://pldr.org/dataset/e6kl0), with data aggregated to MSOA level.
Keywords: COVID-19, Vulnerability index, long-term health conditions, overcrowded housing, care home beds, ethnicity
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