Hurricane Evacuation Capability of Older Adults in Pinellas County, Florida

Research Questions: Does household size affect hurricane evacuation capability in Pinellas County? Does age and household size affect the hurricane evacuation capability of married households in Pinellas County? Does age and household size affect the hurricane evacuation capability of single households in Pinellas County? Background: In September 2022, Hurricane Ian made landfall near Cayo Costa, FL as a Category 5 hurricane with 148 deaths—majority 55 and older. Further research is needed to understand factors that hinder older adults from evacuating. Methods: An evacuation survey conducted following Hurricane Ian in Pinellas County (n = 1239) included 53.4% (n = 662) aged 55+. Chi-square tests were preformed to examine the relationship between age, household size, and marital status with their decision to evacuate. Results: The association between household size and evacuation decisions is statistically significant (8.91, p = 0.01), while age and evacuation decisions among individuals who are not married nor have a domestic partner was found to have a statistically significant (6.43,p = 0.04) association as well. It can be hypothesized that those who are not married or do not have a domestic partner are more likely to evacuate. Additional barriers to evacuation are pets and traffic which contributed to 51.4% and 40.7% of evacuation decisions by older adults respectively. More elaborated statistical analysis needs to be done to address these barriers. Conclusion: Understanding how the composition of a household and its relationship with evacuation decisions can help emergency management develop more targeted messaging to improve evacuation intentions.

The Weather Climate and Society REU program invited 10 students from across the US to conduct research projects related to disaster-vulnerable communities in Florida and other extreme weather-affected areas. These projects were interdisciplinary, integrating social science and physical science aspects of severe weather, climate, and related disasters through field work, interviews, and/or spatial analysis of secondary data in GIS. The PI of this REU is Dr. Jennifer Collins.