Contrasting pre-vaccine COVID-19 waves in Italy through functional data analysis.

This study analyzes mortality patterns during two pre-vaccine COVID-19 waves in Italy, using data from its 107 provinces. Mortality is examined alongside information on mobility, governmental restrictions, and socio-demographic, infrastructural, and environmental factors using Functional Data Analysis tools. Publicly available differential mortality data and local mobility data from Google are processed with smoothing splines and aligned through landmark registration. The resulting curves are clustered to identify mortality patterns, and regression models are used to evaluate the impact of mobility, restrictions, and other factors on mortality. We find significant differences between the two waves: the first had higher, more concentrated mortality peaks, while the second was more widespread and asynchronous. Our results also support the effectiveness of timely restrictions in curbing mortality, and a strong positive association between local mobility and mortality in both pre-vaccine waves. Despite data quality limitations, our findings strengthen the evidence for the role of government restrictions and mobility controls during the pandemic.