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P47 Interrogating structural inequalities in COVID-19 mortality in England and Wales
  1. Gareth Griffith1,2,
  2. George Davey Smith1,2,
  3. David Manley4,
  4. Laura Howe1,2,
  5. Gwilym Owen3
  1. 1Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
  2. 2Population Health Sciences, Bristol Medical School, Bristol, UK
  3. 3Department of Public Health and Policy, University of Liverpool, Liverpool, UK
  4. 4School of Geographical Sciences, University of Bristol, Bristol, UK


Background Numerous observational studies have highlighted structural inequalities in COVID-19 mortality in the UK. Such studies often fail to consider the complex spatial nature of such inequalities in their analysis, leading to the potential for bias and an inability to reach conclusions about the most appropriate structural levels for policy intervention.

Methods We use publicly available population data on COVID-19 related- and all-cause mortality between March and July 2020 in England and Wales to investigate the spatial scale of such inequalities. We propose a multiscale approach to simultaneously consider four spatial scales at which processes driving inequality may act and apportion inequality between these.

Results Adjusting for population age structure, number of care homes and residing in the North we find highest regional inequality in March and June/July. We find finer-grained within-region increased steadily from March until July. The importance of spatial context increases over the study period. No analogous pattern is visible for non-COVID mortality. Higher relative deprivation is associated with increased COVID-19 mortality at all stages of the pandemic but does not explain structural inequalities.

Conclusion Results support initial stochastic viral introduction in the South, with initially high inequality decreasing before the establishment of regional trends by June and July, prior to reported regionality of the ‘second-wave’. We outline how this framework can help identify structural factors driving such processes, and offer suggestions for a long-term, locally-targeted model of pandemic relief in tandem with regional support to buffer the social context of the area.

  • COVID-19 Mortality
  • Inequalities
  • Multilevel Modelling

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