Unraveling spatial patterns of COVID-19 in Italy: Global forces and local economic drivers

Abstract

This article investigates the spatial patterns of coronavirus disease 2019 (COVID-19) infection in Italy and its determinants from March 9 to June 15, 2020, a time interval covering the so-called first wave of COVID pandemics in Europe. The results, based on negative binomial regressions and linear spatial models, confirm the importance of multiple factors that positively correlate with the number of recorded cases. Economic forces, including urban agglomeration, industrial districts, concentration of large companies (both before and after the beginning of the ‘lockdown’) and a north–south gradient, are the most significant predictors of the strength of COVID-19 infection. These effects are statistically more robust in the spatial models than in the aspatial ones. We interpretate our results in the light of pitfalls related to data reliability, and we discuss policy implications and possible avenues for future research.