TY - ABST T1 - Mobile phone data analytics against the COVID-19 epidemics in Italy: flow diversity and local job markets during the national lockdown Y1 - 2020 A1 - Pietro Bonato A1 - Paolo Cintia A1 - Francesco Fabbri A1 - Daniele Fadda A1 - Fosca Giannotti A1 - Pier Luigi Lopalco A1 - Sara Mazzilli A1 - Mirco Nanni A1 - Luca Pappalardo A1 - Dino Pedreschi A1 - Francesco Penone A1 - S Rinzivillo A1 - Giulio Rossetti A1 - Marcello Savarese A1 - Lara Tavoschi AB - Understanding collective mobility patterns is crucial to plan the restart of production and economic activities, which are currently put in stand-by to fight the diffusion of the epidemics. In this report, we use mobile phone data to infer the movements of people between Italian provinces and municipalities, and we analyze the incoming, outcoming and internal mobility flows before and during the national lockdown (March 9th, 2020) and after the closure of non-necessary productive and economic activities (March 23th, 2020). The population flow across provinces and municipalities enable for the modelling of a risk index tailored for the mobility of each municipality or province. Such an index would be a useful indicator to drive counter-measures in reaction to a sudden reactivation of the epidemics. Mobile phone data, even when aggregated to preserve the privacy of individuals, are a useful data source to track the evolution in time of human mobility, hence allowing for monitoring the effectiveness of control measures such as physical distancing. We address the following analytical questions: How does the mobility structure of a territory change? Do incoming and outcoming flows become more predictable during the lockdown, and what are the differences between weekdays and weekends? Can we detect proper local job markets based on human mobility flows, to eventually shape the borders of a local outbreak? UR - https://arxiv.org/abs/2004.11278 ER -