ArticleScientific reports2022
Location intelligence reveals the extent, timing, and spatial variation of hurricane preparedness.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 25 citations in OpenAlex.
- A cross-sectional study on disaster adaptation and resilience among residents in Guangdong Province, China and analysis of its influencing factors.BMC public health · 2026Article
- Location intelligence unveils seasonal spatiotemporal pattern shifts of habitat use and selection by cattle across a South Texas coastal landscape infested withCurrent research in parasitology & vector-borne diseases · 2025Article
- Has the COVID-19 pandemic enhanced the capacity of rural public health emergency management? Evidence from Jiangsu Province of China.Frontiers in public health · 2025Article
- Human mobility networks manifest dissimilar resilience characteristics at macroscopic, substructure, and microscopic scales.Scientific reports · 2023Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hurricanes are one of the most catastrophic natural hazards faced by residents of the United States. Improving the public's hurricane preparedness is essential to reduce the impact and disruption of hurricanes on households. Inherent in traditional methods for quantifying and monitoring hurricane preparedness are significant lags, which hinder effective monitoring of residents' preparedness in advance of an impending hurricane. This study establishes a methodological framework to quantify the extent, timing, and spatial variation of hurricane preparedness at the census block group level using high-resolution location intelligence data. Anonymized cell phone data on visits to points-of-interest for each census block group in Harris County before 2017 Hurricane Harvey were used to examine residents' hurricane preparedness. Four categories of points-of-interest, grocery stores, gas stations, pharmacies and home improvement stores, were identified as they have close relationship with hurricane preparedness, and the daily number of visits from each CBG to these four categories of POIs were calculated during preparation period. Two metrics, extent of preparedness and proactivity, were calculated based on the daily visit percentage change compared to the baseline period. The results show that peak visits to pharmacies often occurred in the early stage of preparation, whereas the peak of visits to gas stations happened closer to hurricane landfall. The spatial and temporal patterns of visits to grocery stores and home improvement stores were quite similar. However, correlation analysis demonstrates that extent of preparedness and proactivity are independent of each other. Combined with synchronous evacuation data, CBGs in Harris County were divided into four clusters in terms of extent of preparedness and evacuation rate. The clusters with low preparedness and low evacuation rate were identified as hotspots of vulnerability for shelter-in-place households that would need urgent attention during response. Hence, the research findings provide a new data-driven approach to quantify and monitor the extent, timing, and spatial variations of hurricane preparedness. Accordingly, the study advances data-driven understanding of human protective actions during disasters. The study outcomes also provide emergency response managers and public officials with novel data-driven insights to more proactively monitor residents' disaster preparedness, making it possible to identify under-prepared areas and better allocate resources in a timely manner.
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