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In 2020, the COVID-19 pandemic has impacted the world, affecting health, economy, education, and social behavior. Much concern was raised about the role of mobility in the diffusion of the disease, with particular attention to public transport. Indeed, understanding the relationship between mobility and the pandemic is key for developing effective public health interventions and policy decisions.

In this work, we aim to understand how mobility, and more specifically mobility by public transport, has affected the diffusion of the pandemic at the regional scale. We focus our attention on Lombardy, the most populated Italian region severely hit by the pandemic in 2020. We explore static mobility data provided by Regione Lombardia, the regional service district, and dynamic mobility data provided by Trenord, a railway operator which serves Lombardy and neighboring areas. We develop an inventive pipeline for the dynamic estimation of Origin-Destination matrices obtained from tickets and passenger counts. This allows us to spot potential triggers in pandemic diffusion enhanced by the concept of proximity induced by mobility. We also develop a novel perspective for assessing the relationship between mobility and overall mortality based upon a functional approach combined with a spatial correlation analysis aimed at identifying the diversified effects on mortality in small geographical areas as a result of the restrictions on mobility introduced to contrast the pandemic.