Infection rates from Covid-19 in Great Britain by geographical units: a model-based estimation from mortality data [Preprint]

Abstract

This study estimates cumulative infection rates from Covid-19 in Great Britain by geographical units 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 between 5 and 6% of people in Great Britain were infected by Covid-19 by the last third of April 2020. It is unlikely that the infection rate was lower than 3% or higher than 12%. Secondly, England had higher infection rates than Scotland and 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 more than 10% 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 in March and April.

Rights

Copyright © 2020 The Author(s). Open Access. This paper is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Identifiers

DOI

https://doi.org/10.31235/osf.io/84f3e

Repository URI

http://hdl.handle.net/10023/20383