Spatio-temporal analysis of the Covid-19 spread in Italy by Bayesian hierarchical models

In this paper, we investigate the spatio-temporal spread pattern of the virus Covid-19 in Italy, during the first wave of infections, from February to October 2020. We provide a disease mapping of the virus infections, by using the Besag-Yorke-Molliè model and its spatio-temporal extensions. Our results confirm the effectiveness of the lockdown action, and show that, during the first wave, the virus spread by an inhomogeneous spatial trend and each province was characterised by a specific temporal trend, independent of the temporal evolution of the observed cases in the other province