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. 2021 Aug;75(8):729-734.
doi: 10.1136/jech-2020-215227. Epub 2021 Feb 4.

How does vulnerability to COVID-19 vary between communities in England? Developing a Small Area Vulnerability Index (SAVI)

Konstantinos Daras  1 , Alexandros Alexiou  2 , Tanith C Rose  2 , Iain Buchan  2 , David Taylor-Robinson  2 , Benjamin Barr  2
Affiliations

How does vulnerability to COVID-19 vary between communities in England? Developing a Small Area Vulnerability Index (SAVI)

Konstantinos Daras et al. J Epidemiol Community Health. 2021 Aug.

Abstract

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.

Methods: We performed a cross-sectional ecological analysis across 6789 small areas in England. We assessed the association between COVID-19 mortality in each area and five vulnerability measures relating to ethnicity, poverty, prevalence of long-term health conditions, living in care homes and living in overcrowded housing. Estimates from multivariable Poisson regression models were used to derive a Small Area Vulnerability Index.

Results: Four vulnerability measures were independently associated with age-adjusted COVID-19 mortality. Each SD 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%, 19% 8% and 11% increase in age-adjusted COVID-19 mortality rate, respectively.

Conclusion: 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. Our analysis indicates the communities who will be most at risk from a second wave of the pandemic.

Keywords: Disease modeling; Health inequalities; PUBLIC HEALTH POLICY.

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Conflict of interest statement

Competing interests: BB, TCR and KD are supported by the NIHR Applied Research Collaboration North West Coast; BB, AA and DT-R are supported by the NIHR School for Public Health Research; DT-R are funded by the Medical Research Council; IB is supported by NIHR Senior Investigator award.

Figures

Figure 1
Figure 1
Association between the predictors and the log COVID-19 age-standardised mortality ratio (SMR). BAME, Black, Asian and Minority Ethnic groups; HH, overcrowded households; IMD; Index of Multiple Deprivation.
Figure 2
Figure 2
COVID-19 vulnerability index at middle layer super output area in England. Greater COVID-19 vulnerability is shown as darker shade of blue. (MAP copyright statement: contains national statistics data crown copyright and database right 2018. Contains ordnance survey data crown copyright and database right 2018).
See this image and copyright information in PMC

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