Measuring the impact of COVID-19 confinement measures on human mobility using mobile positioning data. A European regional analysis
Measuring the impact of COVID-19 confinement measures on human mobility using mobile positioning data. A European regional analysis
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DOI：
10.1016/j.ssci.2020.104925
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发表时间：
2020-12-01
期刊：
影响因子：
6.1
通讯作者：
Vespe, Michele
中科院分区：
文献类型：
--
作者：
Santamaria, Carlos;Sermi, Francesco;Vespe, Michele
这项工作提出了一个移动性指标，来自完全匿名和聚合的移动的定位数据。尽管该指标并不提供有关个人行为的资料，但它捕捉了有关欧盟人口流动模式的宝贵见解，并有望为应对COVID-19疫情提供信息。进行了时空协调，以便该指标可以提供欧洲各国可比的流动性估计。这些指标是以高空间粒度（最高为NUTS 3）提供的。作为应用，该指标用于研究COVID-19限制措施对欧洲流动性的影响。据发现，流动模式的变化很大一部分可以解释这些措施。本文还提出了一个比较分析之间的流动性和感染繁殖数R-t随着时间的推移。这些研究结果将支持政策制定者制定最佳的数据驱动方法，以摆脱限制，绘制封锁措施的社会经济影响，并在新疫情爆发的情况下建立未来情景。
This work presents a mobility indicator derived from fully anonymised and aggregated mobile positioning data. Even though the indicator does not provide information about the behaviour of individuals, it captures valuable insights into the mobility patterns of the population in the EU and it is expected to inform responses against the COVID-19 pandemic. Spatio-temporal harmonisation is carried out so that the indicator can provide mobility estimates comparable across European countries. The indicators are provided at a high spatial granularity (up to NUTS3). As an application, the indicator is used to study the impact of COVID-19 confinement measure on mobility in Europe. It is found that a large proportion of the change in mobility patterns can be explained by these measures. The paper also presents a comparative analysis between mobility and the infection reproduction number R-t over time. These findings will support policymakers in formulating the best data-driven approaches for coming out of confinement, mapping the socio-economic effects of the lockdown measures and building future scenarios in case of new outbreaks.