利用通话详细记录分析境内流离失所者的流动情况，估计抵御自然灾害的能力
Estimating the resilience to natural disasters by using call detail records to analyse the mobility of internally displaced persons
摘要：
我们使用手机通话详细记录来估计一个子集的个人，以前已确定为国内流离失所者（IDPs）突发灾难后的重新安置时间。四种不同的流动性指标--两种版本的回转半径和两种版本的熵--被用来研究三场灾难中人口的行为--2010年海地地震、2015年尼泊尔廓尔喀地震和2016年海地飓风马修。我们用灾难发生后每周仍处于混乱状态的个人的比例来衡量受灾人口重新安置的速度。我们发现，这一比率可以很好地模拟为两个指数衰减的总和，并观察到所有三次灾害的重新安置率是相似的，在灾害发生后的四到五周内，重新安置的流离失所者人数是原来人数的一半。如果对进一步灾害的研究导致观察到类似的指数衰减率，那么这将意味着任何时候的国内流离失所者人数都可以从灾害发生后立即估计的国内流离失所者最初人数中推断出来。或者，该方法提供了一种监测灾难恢复能力和比较灾难恢复率的方法。该方法的优点是不需要对重新安置的地点或时间作出任何假设。我们的研究结果表明，CDR可以显着有助于测量和预测流离失所的持续时间，距离和位置的国内流离失所者在灾后的情况。我们认为，专门开发的CDR分析提供的信息和估计，加上实地数据收集和传统的调查方法，可以帮助对自然灾害的人道主义反应和随后的重新安置工作。
英文摘要：
We use mobile phone call detail records to estimate the resettlement times of a subset of individuals that have been previously identified to be internally displaced persons (IDPs) following a sudden-onset disaster. Four different mobility metrics - two versions of radius of gyration and two versions of entropy - are used to study the behaviour of populations during three disasters - the 2010 earthquake in Haiti, the 2015 Gorkha earthquake in Nepal, and Hurricane Matthew in Haiti in 2016. We characterise the rate at which a disrupted population resettles by the fraction of individuals who remain disrupted each week after the disaster. We find that this rate can be modelled very well as the sum of two exponential decays and observe that the resettling rate for all three disasters is similar, with half the original number of displaced persons having resettled within four to five weeks of the disaster. If the study of further disasters leads to the observation of similar exponential decay rates, then it would imply that the number of IDPs at any time can be inferred from an estimate of the initial number of IDPs immediately following the disaster. Alternatively, the method provides a way to monitor disaster resilience and compare recovery rates across disasters. The method has the advantage that no assumptions need to be made regarding the location or time of resettlement. Our results indicate that CDRs can significantly contribute to measuring and predicting displacement durations, distances, and locations of IDPs in post-disaster scenarios. We believe that information and estimates provided by specifically developed CDR analytics, coupled with field data collection and traditional survey methods, can assist the humanitarian response to natural disasters and the subsequent resettlement efforts.
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