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This project presents methodology to analyze high resolution connected vehicle data (CVD) for understanding how movements of populations during pandemic-hurricanes impact disease spread and devising better plans for safe sheltering and evacuations of vulnerable populations. The dataset contains historical vehicular movement data of for Florida Panhandle Counties of Calhoun, Escambia, Liberty, Gadsden, Jackson, Santa Rosa, Washington and Bay that are impacted by Hurricane Sally which made landfall on September 16, 2020. This coincided with the first phase of the Covid-19 pandemic. The datasets used for this study consist of GPS movement data, shelter and lodging facility wait time, and vehicle count data for 44 shelters and 123 lodging facilities in Florida’s Santa Rosa, Escambia, and Okaloosa counties from 01 to 30 September 2020. The dataset has been used in the following publications: Tsekeni, D.E., Alisan, O., Yang, J., Vanli, O. A., Ozguven, E.E., (2025) “Spatiotemporal modeling of connected vehicle data: An application to non-congregate shelter planning during hurricane-pandemics”, Applied Sciences, 15, 3185. DOI: 10.3390/app15063185. Tsekeni, D.E., Vanli, O. A., (2025) “Time Series Segmentation of Movement Network Data for Endemic-Epidemic Modeling of Infectious Diseases”, IISE Transactions on Healthcare Systems Engineering, (Submitted, May 2025)