As the news media reported these headlines, neither the Italian public nor the Italian authorities appeared to perceive an imminent threat, though retrospective analyses now suggest that the virus may have been circulating in the north of the country as far back as December 2019 (e.g., detection of SARS-CoV-2 in the wastewater of Milan and Turin 1). At the beginning of February, a group of Italian citizens was repatriated from Wuhan – among them, one tested positive. The techniques we describe could capture additional and potentially sharper signals if applied to richer data.Īt the end of January 2020, two Chinese tourists were hospitalized in Rome and tested positive to SARS-CoV-2.
Among the latter, primary care appears to mitigate mortality, and contacts in hospitals, schools and workplaces to aggravate it. We find that mobility and positivity can predict COVID-19 mortality, also when controlling for relevant covariates. These depict two starkly different epidemics an “exponential” one unfolding in Lombardia and the worst hit areas of the north, and a milder, “flat(tened)” one in the rest of the country-including Veneto, where cases appeared concurrently with Lombardia but aggressive testing was implemented early on. Notwithstanding limitations in accuracy and resolution of the data available from public sources, we pinpoint significant trends exploiting information in curves and shapes with Functional Data Analysis techniques. We investigate patterns of COVID-19 mortality across 20 Italian regions and their association with mobility, positivity, and socio-demographic, infrastructural and environmental covariates.
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