Understanding dynamic human mobility changes and spatial interaction patterns at different geographic scales is crucial for assessing the impacts of non-pharmaceutical interventions (such as stay-at-home orders) during the COVID-19 pandemic. In this data descriptor, we introduce a regularly-updated multiscale dynamic human mobility flow dataset across the United States, with data starting from March 1st, 2020. By analysing millions of anonymous mobile phone users’ visits to various places provided by SafeGraph, the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state. There is high correlation between our mobility flow dataset and openly available data sources, which shows the reliability of the produced data. Such a high spatiotemporal resolution human mobility flow dataset at different geographic scales over time may help monitor epidemic spreading dynamics, inform public health policy, and deepen our understanding of human behaviour changes under the unprecedented public health crisis. This up-to-date O-D flow open data can support many other social sensing and transportation applications. Measurement(s) mobility • Interaction Technology Type(s) GPS navigation system • machine learning Factor Type(s) geographic scale • temporal interval • geographic location • spatiotemporal region Sample Characteristic – Location United States of America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13135085
【저자키워드】 Infectious diseases, Socioeconomic scenarios, Geography, 【초록키워드】 public health, reliability, COVID-19 pandemic, technology, Intervention, public health crisis, Epidemic, Impact, Metadata, understanding, location, dataset, change, Support, Factor, available data, geographic location, high correlation, help, America, MONITOR, The United States, spatiotemporal, produced, Sample, reported, United State, provided, interaction pattern, 【제목키워드】 dataset, COVID-19 epidemic,