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However, there are many scenarios (e.g., spreading diseases, migration) in which timely data on international commuters are vital. Mobile phones represent a unique opportunity to monitor international mobility flows in a timely manner and with proper spatial aggregation. This work proposes using roaming data generated by mobile phones to model incoming and outgoing international mobility. We use the gravity and radiation models to capture mobility flows before and during the introduction of non-pharmaceutical interventions. However, traditional models have some limitations: for instance, mobility restrictions are not explicitly captured and may play a crucial role. To overtake such limitations, we propose the COVID Gravity Model (CGM), namely an extension of the traditional gravity model that is tailored for the pandemic scenario. This proposed approach overtakes, in terms of accuracy, the traditional models by 126.9% for incoming mobility and by 63.9% when modeling outgoing mobility flows.<\/jats:p>","DOI":"10.1140\/epjds\/s13688-022-00335-9","type":"journal-article","created":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T13:04:01Z","timestamp":1649077441000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Modeling international mobility using roaming cell phone traces during COVID-19 pandemic"],"prefix":"10.1140","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6964-9877","authenticated-orcid":false,"given":"Massimiliano","family":"Luca","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruno","family":"Lepri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrique","family":"Frias-Martinez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andra","family":"Lutu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,4,4]]},"reference":[{"key":"335_CR1","volume-title":"Move: the forces uprooting us","author":"P Khanna","year":"2021","unstructured":"Khanna P (2021) Move: the forces uprooting us. 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All datasets used in this work are covered by NDAs, prohibiting any re-sharing with 3rd parties even for research purposes. Further, raw data has been reviewed and validated by the operator with respect to GPDR compliance (e.g., no identifier can be associated to person), and data processing only extracts aggregated user information at postcode level. No personal and\/or contract information was available for this study and none of the authors of this paper participated in the extraction and\/or encryption of the raw data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"22"}}