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

Author:

Rawson ThomasORCID,Hinsley Wes,Sonabend Raphael,Semenova Elizaveta,Cori Anne,Ferguson Neil M

Abstract

AbstractConsiderable spatial heterogeneity has been observed in COVID-19 transmission across administrative regions of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 administrative regions of England across 95 weeks, fit using a Bayesian evidence synthesis framework. We include the mechanistic 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 regionally-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 mechanistic impact of these terms was of negligible impact compared to the role of spatial exportation between regions. While these results confirm the impact of some, but not all, measures of regional inequity in England, our work corroborates the finding that observed differences in regional disease transmission during the pandemic were predominantly driven by underlying epidemiological factors rather than the demography and health inequity between regions.Author SummaryDuring 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.

Publisher

Cold Spring Harbor Laboratory

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