{"year":"2021","isi":1,"external_id":{"isi":["000662554703032"],"arxiv":["2008.10064"]},"publication_identifier":{"isbn":["9781728162515"]},"publication":"2020 IEEE International Conference on Big Data","author":[{"full_name":"Heiler, Georg","last_name":"Heiler","first_name":"Georg"},{"full_name":"Reisch, Tobias","last_name":"Reisch","first_name":"Tobias"},{"full_name":"Hurt, Jan","last_name":"Hurt","first_name":"Jan"},{"full_name":"Forghani, Mohammad","last_name":"Forghani","first_name":"Mohammad"},{"first_name":"Aida","last_name":"Omani","full_name":"Omani, Aida"},{"full_name":"Hanbury, Allan","last_name":"Hanbury","first_name":"Allan"},{"orcid":"0000-0001-6746-4174","id":"2A2BCDC4-CF62-11E9-BE5E-3B1EE6697425","full_name":"Karimipour, Farid","last_name":"Karimipour","first_name":"Farid"}],"page":"3123-3132","doi":"10.1109/bigdata50022.2020.9378374","_id":"9253","language":[{"iso":"eng"}],"citation":{"ieee":"G. Heiler <i>et al.</i>, “Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic,” in <i>2020 IEEE International Conference on Big Data</i>, Atlanta, GA, United States, 2021, pp. 3123–3132.","mla":"Heiler, Georg, et al. “Country-Wide Mobility Changes Observed Using Mobile Phone Data during COVID-19 Pandemic.” <i>2020 IEEE International Conference on Big Data</i>, IEEE, 2021, pp. 3123–32, doi:<a href=\"https://doi.org/10.1109/bigdata50022.2020.9378374\">10.1109/bigdata50022.2020.9378374</a>.","short":"G. Heiler, T. Reisch, J. Hurt, M. Forghani, A. Omani, A. Hanbury, F. Karimipour, in:, 2020 IEEE International Conference on Big Data, IEEE, 2021, pp. 3123–3132.","ama":"Heiler G, Reisch T, Hurt J, et al. Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic. In: <i>2020 IEEE International Conference on Big Data</i>. IEEE; 2021:3123-3132. doi:<a href=\"https://doi.org/10.1109/bigdata50022.2020.9378374\">10.1109/bigdata50022.2020.9378374</a>","apa":"Heiler, G., Reisch, T., Hurt, J., Forghani, M., Omani, A., Hanbury, A., &#38; Karimipour, F. (2021). Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic. In <i>2020 IEEE International Conference on Big Data</i> (pp. 3123–3132). Atlanta, GA, United States: IEEE. <a href=\"https://doi.org/10.1109/bigdata50022.2020.9378374\">https://doi.org/10.1109/bigdata50022.2020.9378374</a>","ista":"Heiler G, Reisch T, Hurt J, Forghani M, Omani A, Hanbury A, Karimipour F. 2021. Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic. 2020 IEEE International Conference on Big Data. Big Data: International Conference on Big Data, 3123–3132.","chicago":"Heiler, Georg, Tobias Reisch, Jan Hurt, Mohammad Forghani, Aida Omani, Allan Hanbury, and Farid Karimipour. “Country-Wide Mobility Changes Observed Using Mobile Phone Data during COVID-19 Pandemic.” In <i>2020 IEEE International Conference on Big Data</i>, 3123–32. IEEE, 2021. <a href=\"https://doi.org/10.1109/bigdata50022.2020.9378374\">https://doi.org/10.1109/bigdata50022.2020.9378374</a>."},"conference":{"name":"Big Data: International Conference on Big Data","start_date":"2020-12-10","end_date":"2020-12-13","location":"Atlanta, GA, United States"},"publisher":"IEEE","scopus_import":"1","oa_version":"Preprint","oa":1,"date_created":"2021-03-21T11:34:07Z","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","quality_controlled":"1","title":"Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic","status":"public","month":"03","article_processing_charge":"No","date_updated":"2023-08-07T14:00:13Z","type":"conference","day":"19","department":[{"_id":"HeEd"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2008.10064"}],"abstract":[{"text":"In March 2020, the Austrian government introduced a widespread lock-down in response to the COVID-19 pandemic. Based on subjective impressions and anecdotal evidence, Austrian public and private life came to a sudden halt. Here we assess the effect of the lock-down quantitatively for all regions in Austria and present an analysis of daily changes of human mobility throughout Austria using near-real-time anonymized mobile phone data. We describe an efficient data aggregation pipeline and analyze the mobility by quantifying mobile-phone traffic at specific point of interests (POIs), analyzing individual trajectories and investigating the cluster structure of the origin-destination graph. We found a reduction of commuters at Viennese metro stations of over 80% and the number of devices with a radius of gyration of less than 500 m almost doubled. The results of studying crowd-movement behavior highlight considerable changes in the structure of mobility networks, revealed by a higher modularity and an increase from 12 to 20 detected communities. We demonstrate the relevance of mobility data for epidemiological studies by showing a significant correlation of the outflow from the town of Ischgl (an early COVID-19 hotspot) and the reported COVID-19 cases with an 8-day time lag. This research indicates that mobile phone usage data permits the moment-by-moment quantification of mobility behavior for a whole country. We emphasize the need to improve the availability of such data in anonymized form to empower rapid response to combat COVID-19 and future pandemics.","lang":"eng"}],"date_published":"2021-03-19T00:00:00Z","publication_status":"published"}