A0672
Title: COVID-19 in Italy: Contrasting pre-vaccine epidemic waves through functional data clustering
Authors: Lorenzo Testa - Carnegie Mellon University (United States) [presenting]
Tobia Boschi - The Pennsylvania State University (United States)
Jacopo Di Iorio - Emory University (United States)
Marzia Cremona - Universite Laval (Canada)
Francesca Chiaromonte - The Pennsylvania State University (United States)
Abstract: Data from 107 Italian provinces is used to characterize and compare mortality patterns during the first two COVID-19 waves before vaccines were introduced. Using functional data analysis clustering techniques, differences between the two waves are documented, focusing on their magnitude and variability. Specifically, while both waves were characterized by a co-occurrence of 'exponential' and 'mild' mortality patterns, the first had higher and more concentrated mortality peaks, while the second spread much more broadly and asynchronously through the country. Notwithstanding limitations in the accuracy and reliability of publicly available data, these patterns are also associated with mobility, the timing of government restrictions, and socio-demographic, infrastructural, and environmental covariates. Evidence of a significant positive association between local mobility and mortality is found in both epidemic waves, and the effectiveness of timely restrictions is corroborated in curbing mortality. The techniques described could capture additional and potentially sharper signals if applied to richer data.
