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The impact of health inequity on spatial variation of COVID-19 transmission in England

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  • Thomas Rawson
  • Wes Hinsley
  • Raphael Sonabend
  • Elizaveta Semenova
  • Anne Cori
  • Neil M Ferguson

Abstract

Considerable spatial heterogeneity has been observed in COVID-19 transmission across administrative areas of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 administrative areas of England across 95 weeks, fit using a Bayesian evidence synthesis framework. We incorporate the impact of acquired immunity, of spatial exportation of cases, and 16 spatially-varying socio-economic, socio-demographic, health, and mobility variables. Model comparison assesses the relative contributions of these respective mechanisms. We find that spatially-varying and time-varying differences in week-to-week transmission were definitively associated with differences in: time spent at home, variant-of-concern proportion, and adult social care funding. However, model comparison demonstrates that the impact of these terms is negligible compared to the role of spatial exportation between administrative areas. While these results confirm the impact of some, but not all, static measures of spatially-varying inequity in England, our work corroborates the finding that observed differences in disease transmission during the pandemic were predominantly driven by underlying epidemiological factors rather than aggregated metrics of demography and health inequity between areas. Further work is required to assess how health inequity more broadly contributes to these epidemiological factors.Author summary: During the COVID-19 pandemic, different geographic areas of England saw different patterns in the number of confirmed cases over time. This study investigated whether demographic differences between these areas (such as the amount of deprivation, the age and ethnicity of the populations, or differences in where people spent their time) were linked to these differences in disease transmission. We also considered whether this was associated with the number of cases in neighbouring areas as well. Using a mathematical model fit to multiple data streams, we discovered that a statistically significant link between some demographic variables (time spent at home, COVID-19 variant, and the amount of adult social care funding) and week-to-week transmission exists, but this relationship is very small, and the influence of cases in neighbouring areas was far more impactful in explaining differences in transmission between areas over time.

Suggested Citation

  • Thomas Rawson & Wes Hinsley & Raphael Sonabend & Elizaveta Semenova & Anne Cori & Neil M Ferguson, 2024. "The impact of health inequity on spatial variation of COVID-19 transmission in England," PLOS Computational Biology, Public Library of Science, vol. 20(5), pages 1-15, May.
    • Handle: RePEc:plo:pcbi00:1012141
    DOI: 10.1371/journal.pcbi.1012141
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    1. Helen Ward & Christina Atchison & Matthew Whitaker & Kylie E. C. Ainslie & Joshua Elliott & Lucy Okell & Rozlyn Redd & Deborah Ashby & Christl A. Donnelly & Wendy Barclay & Ara Darzi & Graham Cooke & , 2021. "SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    2. Giorgino, Toni, 2009. "Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i07).
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