Representativeness of mobile phone location data for accurate measurement of population movement

人类旅行被用作一系列社会行为的代理，包括移民、经济参与、社会关系和传染病的传播。手机的广泛使用极大地提高了科学家收集旅行模式信息的能力。虽然移动电话位置数据提供了关于经验移动模式的不可否认的有用信息，但这些数据可能是从不能代表其意图代表的更广泛人群的个人样本中收集的。这项研究将解决移动电话位置数据中包含的个人样本是否在空间、行为或人口统计特征方面存在偏见，以及这些数据集中捕获的运动是否准确地代表了特定的社会行为。这项研究将特别侧重于使用移动电话位置数据来预测传染病传播。研究领域：人文地理学、人口学、社会学研究目的：1.主要目的是了解地理、社会和经济因素是如何影响新冠肺炎期间的出行行为的。我将探索流动数据的代表性，以及某些人口群体或流动类型是代表不足还是代表过高。重要的是，这将为将个体样本的移动概括为整个群体的行为的方法提供信息。我将研究对紧急情况下行动行为的预测，以及如何利用有关人口的社会人口特征的信息来改进这些预测。我将调查隐私保护聚合技术(空间和时间)如何影响移动指标，以及这些指标对不同社会人口群体的影响。详细的研究问题：我将使用移动数据来量化英国移动行为的各种地理、社会和经济决定因素。与我以前的工作一样，这项研究将特别应用于了解突发公共卫生事件期间的运动模式，包括应对新冠肺炎大流行和相关干预措施。这项研究还将对运动模式进行预测，并确定人口因素如何改善对人类运动预测的表现。最后，研究将确定隐私保护聚合和审查方法对人体运动指标解释的影响。

Human travel is used as a proxy for a range of social behaviors including migration, economic engagement, social connections, and the transmission of infectious disease. The widespread adoption of mobile phones has greatly enhanced scientists' ability to collect information on patterns of travel. While mobile phone location data provides undeniably useful information on empirical patterns of movement, this data may be collected from a sample of individuals which is not representative of the broader population which it is intended to represent. This research will address whether the sample of individuals included in mobile phone location data is biased with respect to spatial, behavioral, or demographic characteristics, and whether the movement captured in these datasets is an accurate proxy of specific social behaviors. This research will focus in particular on the use of mobile phone location data for predicting infectious disease transmission. Research Areas: human geography, demography, sociologyAims of the research:1. The principal aim is to understand how geographic, social, and economic factors influence movementbehaviour during the COVID-19 pandemic.2. I will explore the representativeness of movement data, and whether certain demographic groups ormovement types are under or overrepresented. Importantly, this will inform methods for generalising themovement of a sample of individuals to the behaviours of an entire population.3. I will examine the prediction of movement behaviour during emergencies and how these predictionscan be improved with information on the socio-demographic characteristics of populations.4. I will investigate how privacy preserving aggregation techniques (spatial and temporal) impactmovement indicators and the effect these indicators have on different socio-demographic groups.Detailed Research Questions: I will use movement data to quantify the varied geographic, social, andeconomic determinants of movement behaviour in the UK. As in my previous work, this research will bespecifically applied to understanding patterns of movement during public health emergencies, includingthe COVID-19 pandemic and associated interventions. The research will also make predictions ofmovement patterns and determine how demographic factors improve the performance of predictions ofhuman movements. Finally, the research will determine the influence of privacy preserving aggregationand censoring methods on the interpretation of human movement indicators.