Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework
Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework
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DOI：
10.1080/13658816.2021.2005796
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发表时间：
2021-12-20
影响因子：
5.7
通讯作者：
Dodge, Somayeh
中科院分区：
文献类型：
--
作者：
Noi, Evgeny;Rudolph, Alexander;Dodge, Somayeh
COVID-19疫情导致本地及全球的流动模式及旅游行为发生深刻变化。因此，研究人员和政策制定者广泛使用移动指标作为研究、建模和减轻COVID-19大流行影响的指标。然而，这些移动性指标的准确性和可变性还没有被研究。本文对美国2020年大流行期间研究人员可用的流动性和社交距离指标进行了系统性综述。对9个不同来源的26个指标的时空覆盖率和县级样本代表性进行了分析和评估。最后，全球和地方的空间关联指标计算，探索空间和时间异质性的移动模式。流动性和社会距离的潜在变化的结构在不同的美国县和不同的数据集进行检查。我们认为，一个单一的措施可能无法完美地描述所有方面的流动性。
The COVID-19 pandemic resulted in profound changes in mobility patterns and altered travel behaviors locally and globally. As a result, movement metrics have widely been used by researchers and policy makers as indicators to study, model, and mitigate the impacts of the COVID-19 pandemic. However, the veracity and variability of these mobility metrics have not been studied. This paper provides a systematic review of mobility and social distancing metrics available to researchers during the pandemic in 2020 in the United States. Twenty-six indices across nine different sources are analyzed and assessed with respect to their spatial and temporal coverage as well as sample representativeness at the county-level. Finally global and local indicators of spatial association are computed to explore spatial and temporal heterogeneity in mobility patterns. The structure of underlying changes in mobility and social distancing is examined in different US counties and across different data sets. We argue that a single measure might not describe all aspects of mobility perfectly.