Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak

In this paper, we present the work conducted by Vodafone to enrich the understanding of people movement in Italy during the outbreak of the Coronavirus in 2020, and the tool developed to support the decisions taken by the authorities during that period. We have developed a solution to anonymously mo...

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Main Authors: Francesco Calabrese, Enrico Cobelli, Vincenzo Ferraiuolo, Giovanni Misseri, Fabio Pinelli, Daniel Rodriguez
Format: Article
Language:English
Published: Cambridge University Press 2021-01-01
Series:Data & Policy
Subjects:
Online Access:https://www.cambridge.org/core/product/identifier/S2632324921000183/type/journal_article
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author Francesco Calabrese
Enrico Cobelli
Vincenzo Ferraiuolo
Giovanni Misseri
Fabio Pinelli
Daniel Rodriguez
author_facet Francesco Calabrese
Enrico Cobelli
Vincenzo Ferraiuolo
Giovanni Misseri
Fabio Pinelli
Daniel Rodriguez
author_sort Francesco Calabrese
collection DOAJ
description In this paper, we present the work conducted by Vodafone to enrich the understanding of people movement in Italy during the outbreak of the Coronavirus in 2020, and the tool developed to support the decisions taken by the authorities during that period. We have developed a solution to anonymously monitor the daily movements of Vodafone SIMs in Italy, at aggregate level, at different spatial and temporal granularity, to provide insights into the movements of Italians.
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spelling doaj.art-d75b942d44c54b209c80a9e0b9673c7e2023-03-09T12:31:34ZengCambridge University PressData & Policy2632-32492021-01-01310.1017/dap.2021.18Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreakFrancesco Calabrese0Enrico Cobelli1Vincenzo Ferraiuolo2Giovanni Misseri3Fabio Pinelli4https://orcid.org/0000-0003-1058-6917Daniel Rodriguez5Big Data and AI, Vodafone, 20147 Milan, ItalyBig Data and AI, Vodafone, 20147 Milan, ItalyBig Data and AI, Vodafone, 20147 Milan, ItalyBig Data and AI, Vodafone, 20147 Milan, ItalyBig Data and AI, Vodafone, 20147 Milan, ItalyBig Data and AI, Vodafone, 20147 Milan, ItalyIn this paper, we present the work conducted by Vodafone to enrich the understanding of people movement in Italy during the outbreak of the Coronavirus in 2020, and the tool developed to support the decisions taken by the authorities during that period. We have developed a solution to anonymously monitor the daily movements of Vodafone SIMs in Italy, at aggregate level, at different spatial and temporal granularity, to provide insights into the movements of Italians.https://www.cambridge.org/core/product/identifier/S2632324921000183/type/journal_articleapplied data sciencemobility analyticsurban dynamics
spellingShingle Francesco Calabrese
Enrico Cobelli
Vincenzo Ferraiuolo
Giovanni Misseri
Fabio Pinelli
Daniel Rodriguez
Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak
Data & Policy
applied data science
mobility analytics
urban dynamics
title Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak
title_full Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak
title_fullStr Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak
title_full_unstemmed Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak
title_short Using Vodafone mobile phone network data to provide insights into citizens mobility in Italy during the Coronavirus outbreak
title_sort using vodafone mobile phone network data to provide insights into citizens mobility in italy during the coronavirus outbreak
topic applied data science
mobility analytics
urban dynamics
url https://www.cambridge.org/core/product/identifier/S2632324921000183/type/journal_article
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