Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake
Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake
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DOI：
10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c
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发表时间：
2016-02
期刊：
影响因子：
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通讯作者：
Robin T. Wilson;E. zu Erbach-Schoenberg;Maximilian Albert;D. Power;S. Tudge;Miguel Gonzalez;Sam Guthrie;Heather R. Chamberlain;C. Brooks;Christopher Hughes;Lenka Pitonakova;C. Buckee;Xin Lu;Erik Wetter;A. Tatem;Linus Bengtsson
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作者：
Robin T. Wilson;E. zu Erbach-Schoenberg;Maximilian Albert;D. Power;S. Tudge;Miguel Gonzalez;Sam Guthrie;Heather R. Chamberlain;C. Brooks;Christopher Hughes;Lenka Pitonakova;C. Buckee;Xin Lu;Erik Wetter;A. Tatem;Linus Bengtsson
导语：突如其来的冲击灾害往往会导致大量的人流离失所。这些转移可能发生在事件发生之前，由于发出预警信息，也可能发生在事件发生后，原因是避难所和生计受损，以及长期重建努力的结果。流离失所的人特别容易受到伤害，往往需要支持。然而，及时和准确地收集关于流离失所人口的人数和目的地的数据极具挑战性，特别是在灾后收集。移动电话通话详细记录被证明是估计2010年海地地震后人口流动的有效数据来源，但它们在自然灾害发生后立即提供人口迁移的近乎实时的持续测量的潜力尚未得到证明。方法：在2015年4月25日尼泊尔地震发生后的9天内，迅速部署了计算架构和分析能力，以便根据1200万未确认身份的移动电话用户的移动情况，从呼叫详细记录中提供对人口迁移的时空详细估计。结果：分析显示了地震后人口流动模式的演变和返回受灾地区的模式，并在很高程度上详细说明了这些模式。尤其值得注意的是，地震发生后，估计有39万人从加德满都山谷迁移到周边地区和尼泊尔中南部人口稠密地区。讨论：这一分析提供了有关自然灾害后人类活动的前所未有的信息，在地震发生后的很短时间内提供。用这种方法揭示的模式几乎不可能通过其他方法找到，人道主义机构对此非常感兴趣。
Introduction: Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated. Methods: A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users. Results: Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal. Discussion: This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.