Analyzing Preparedness to Disaster Types and Severity: Insights from Human Mobility Data

Abstract

Our understanding of human response, preparation, and resilience to natural disasters remains limited despite their increasing frequency and severity. Traditional preparedness and recovery models predominantly depend on census data, which, while insightful, fail to capture recovery trajectories over time. This study adds a more dynamic aspect to preparedness models by leveraging human mobility data to address two intertwined objectives: understanding how preparedness patterns change across disaster types and examining the impact of communities' demographic and socioeconomic characteristics. Mobility was tracked using cell phone data to monitor visitation patterns in three disaster-affected locations: Hurricane Ian in Lee County, Florida; flooding in Breathitt County, Kentucky; and Hurricane Sally in Baldwin County, Alabama. The daily number of visits from each Census Block Group (CBG) to points of interest (POIs) was calculated, and preparedness was assessed by the percentage of change in daily visits prior to a disaster compared to a baseline. Ordinary Least Squares (OLS) regression was used to determine the impact of demographic and socioeconomic variables on preparedness. Key findings indicate that the type of disaster significantly affects mobility and preparedness levels. Predictable disasters like hurricanes led to more preparedness actions, while unpredictable ones like Kentucky flash floods (-27.27%) resulted in less. Hurricane Sally (Category 2) saw increased preparedness (+2.59% mobility), whereas Hurricane Ian (Category 4) saw a slight decrease (-0.21%). Socio-economic characteristics variably influenced disaster preparedness, with higher education correlating with greater preparedness in Baldwin County. Older adults in Lee County showed greater readiness but lower evacuation rates, while higher road density and higher median income were linked to lower preparedness. Coastal proximity in Lee County correlated with higher preparedness. The research highlights the critical role of human mobility data in assessing disaster preparedness and recovery, showing that predictability affects preparedness, with hurricanes prompting more activities than flash floods. It underscores the need for tailored preparedness approaches based on community characteristics, emphasizing that higher income or education levels do not ensure better preparedness and highlighting the complex interplay of socio-economic, demographic, and geographic factors.