Time courses of COVID-19 infection and local variation in socioeconomic and health disparities in England

Liu, S. H.; Liu, B.; Li, Y.; Norbury, A.

Objective: To identify factors associated with local variation in the time course of COVID-19 case burden in England. Methods: We analyzed laboratory-confirmed COVID-19 case data for 150 upper tier local authorities, from the period from January 30 to May 6, 2020, as reported by Public Health England. Using methods suitable for time-series data, we identified clusters of local authorities with distinct trajectories of daily cases, after adjusting for population size. We then tested for differences in sociodemographic, economic, and health disparity factors between these clusters. Results: Two clusters of local authorities were identified: a higher case trajectory that rose faster over time to reach higher peak infection levels, and a lower case trajectory cluster that emerged more slowly, and had a lower peak. The higher case trajectory cluster (79 local authorities) had higher population density (p<0.001), higher proportion of Black and Asian residents (p=0.03; p=0.02), higher multiple deprivation scores (p<0.001), a lower proportions of older adults (p=0.005), and higher preventable mortality rates (p=0.03). Local authorities with higher proportions of Black residents were more likely to belong to the high case trajectory cluster, even after adjusting for population density, deprivation, proportion of older adults and preventable mortality (p=0.04). Conclusion: Areas belonging to the trajectory with significantly higher COVID-19 case burden were more deprived, and had higher proportions of ethnic minority residents. A higher proportion of Black residents in regions belonging to the high trajectory cluster was not fully explained by differences in population density, deprivation, and other overall health disparities between the clusters.