Skip to main content
Dryad

Data from: Disparate patterns of movements and visits to points of interest located in urban hotspots across U.S. metropolitan cities during COVID-19

Cite this dataset

Li, Qingchun (2020). Data from: Disparate patterns of movements and visits to points of interest located in urban hotspots across U.S. metropolitan cities during COVID-19 [Dataset]. Dryad. https://doi.org/10.5061/dryad.cvdncjt21

Abstract

We examined the effect of social distancing on changes in visits to urban hotspot points of interest. In a pandemic situation, urban hotspots could be potential superspreader areas as visits to urban hotspots can increase the risk of contact and transmission of a disease among a population. We mapped origin-destination networks from census block groups to points of interest (POIs), such as restaurants, museums, and schools, in sixteen cities in the United States. We adopted a coarse-grain approach to examine patterns of visits to POIs among hotspots and non-hotspots from January to May 2020. Also, we conducted chi-square tests to identify POIs with significant flux-in changes during the analysis period. The results showed disparate patterns across cities in terms of reduction in hotspot POI visits. Sixteen cities are divided into two categories. In one category, which includes the cities of, San Francisco, Seattle, and Chicago, we observe a considerable decrease in hotspot POI visits, while in another category, including the cites of, Austin, Houston, and San Diego, the visits to hotspots did not greatly decrease. While all the cities exhibited overall decreasing visits to POIs, one category maintained the proportion of visits to hotspot POIs. The proportion of visits to some POIs (e.g., Restaurants) remained stable during the social distancing period, while some POIs had an increased proportion of visits (e.g., Grocery Stores). We also identified POIs with significant flux-in changes, showing that related businesses were greatly affected by social distancing.

Methods

SafeGraph provided the raw data: https://docs.safegraph.com/docs/weekly-patterns.

Funding

National Science Foundation, Award: 2026814