The spatial spread of infection rates at the dawn of a pandemic: A socioeconomic approach

This paper presents an innovative examination of the spread of COVID-19 infection rates across England over a seven-week period commencing prior to the initial lockdown and continuing until the relaxation of some COVID-19 lockdown restrictions. We examine the evolution in infection rates across socioeconomic characteristics using topological data analysis to map the joint distribution of socioeconomic characteristics and identify where and when infection rates grew differentially. Although the over 65s and those with chronic health conditions were socioeconomic groups most at risk of experiencing morbidity and mortality from COVID-19, these socioeconomic correlates reflect consequences of the spread rather than the carriers of the virus and the reasons for the spread. Our empirical results present new findings that International Territorial Level 3 areas with higher proportions of younger inhabitants who worked longer hours for higher pay experienced earlier and faster rates of increase in infections, and that commuter towns and rural areas lagged their urban metropolises in terms of infection rates. These results underscore who was infected, where labour market characteristics associated with infection rates interact across space, and the need to improve understanding of when and why areas experienced higher infection rates. This is the first paper to find that the spread of the COVID-19 virus in the UK was greater where there was a relative abundance of skilled workers who have greater professional geographical mobility.