Country-wide Mobility Changes Observed Using Mobile Phone Data During COVID-19 Pandemic

被引:48
作者
Heiler, Georg [1 ,2 ]
Reisch, Tobias [2 ,3 ]
Hurt, Jan [2 ]
Forghani, Mohammad [4 ]
Omani, Aida [4 ]
Hanbury, Allan [1 ,2 ]
Karimipour, Farid [5 ]
机构
[1] TU Wien, Inst Informat Syst Engn, Favoritenstr 9-11, A-1040 Vienna, Austria
[2] Complex Sci Hub, Josefstdter Str 39, A-1080 Vienna, Austria
[3] Med Univ Vienna, Inst Complex Syst, Spilalgasse 23, A-1090 Vienna, Austria
[4] Coll Engn, Sch Surveying & Geospatial Engn, North Kargar Ave, Tehran, Iran
[5] Inst Sci & Technol IST, Edelsbrunner Grp, Campus 1, A-3400 Klosterneuburg, Austria
来源
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2020年
基金
奥地利科学基金会;
关键词
big-data; call-data-records (CDR) Apache-Spark; graph-analysis; mobility; URBAN; PATTERNS;
D O I
10.1109/BigData50022.2020.9378374
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 I schgl (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.
引用
收藏
页码:3123 / 3132
页数:10
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