Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 13, 2023 erstellt
Beschreibung:
This article explores how improvements in the understanding of socioeconomic characteristics and their interactions across small geographical areas could enable more efficient resource allocations to counteract the spread of a disease. Our empirical analysis focusses on COVID-19 infection rates across English NUTS3 regions over a seven-week period commencing prior to the initial lockdown and continuing until the relaxation of some COVID-19 lockdown restrictions. The over 65s and those with chronic health conditions were the socioeconomic groups most at risk of experiencing morbidity and mortality, but these socioeconomic correlates reflect the consequences of the spread rather than the carriers of the disease. Our empirical analysis reveals that 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 behind their urban metropolises in terms of infection rates. These results defy expectations based purely on transportation flows and physical geography, and instead emphasise the need to increase understanding of how spatially varying labour market characteristics are associated with the spread of contagious diseases