Infection rates from Covid-19 in Great Britain by geographical units: A model-based estimation from mortality data. (January 2021) - Kulu, Hill; Dorey, Peter
Abstract: This study estimates cumulative infection rates from Covid-19 in Great Britain by local authority districts (LADs) and council areas (CAs) and investigates spatial patterns in infection rates. We propose a model-based approach to calculate cumulative infection rates from data on observed and expected deaths from Covid-19. Our analysis of mortality data shows that 7% of people in Great Britain were infected by Covid-19 by the last third of June 2020. It is unlikely that the infection rate was lower than 4% or higher than 15%. Secondly, England had higher infection rates than Scotland and especially Wales, although the differences between countries were not large. Thirdly, we observed a substantial variation in virus infection rates in Great Britain by geographical units. Estimated infection rates were highest in the capital city of London where between 11 and 12% of the population might have been infected and also in other major urban regions, while the lowest were in small towns and rural areas. Finally, spatial regression analysis showed that the virus infection rates increased with the increasing population density of the area and the level of deprivation. The results suggest that people from lower socioeconomic groups in urban areas (including those with minority backgrounds) were most affected by the spread of coronavirus from March to June. Highlights: About 7% of people in Great Britain were infected by Covid-19 by the last third of June 2020. Infection rates were highest in the capital city of London where between 11 and 12% of the population might have been infected, while they were the lowest in small towns and rural areas. The virus has hit harder in areas of higher deprivation in cities, exacerbating existing social and spatial inequalities.