Pandemic Spreading in Italy and Regional Policies: An Approach with Self-organizing Maps

The purpose of the chapter is using machine learning techniques (namely Self-Organizing Maps) to catch the emergence of clusters among Italian regions that can eventually contribute to explain the different behaviour of the pandemic within the same country. To do this, we have considered demographic, healthcare, and political data at regional level and we have tried going to the root of interactions among them. In this way, we obtained a model of the relations among variables with good explanatory capabilities, a kind of early-warning system which we hope could be helpful to address further intervention in the battle against COVID-19 pandemic.