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This paper presents data on Prolonged Unplanned School Closures (PUSCs) caused by hurricanes and affecting school districts along the East and Gulf Coasts of the United States between the 2011/12 and 2018/19 academic years. PUSCs are school closures lasting at least seven days that were not part of the school calendar at the start of the academic year. The dataset additionally includes counterfactual observations, meaning information pertaining to school districts affected by hurricanes, but that either did not close, or that did not experience a prolonged closure. We additionally incorporate school-district level data on socioeconomic characteristics, geography, school district capacity, and hazard characteristics. These data are used in the paper titled “Learning after the storm: Characterizing and Understanding Prolonged Unplanned School Closures After Hurricane". This dataset can be leveraged to uncover patterns of PUSCs, evaluate the impacts of various factors on school closure duration, and identify appropriate policies and strategies to enhance community resilience by minimizing the potential and the impacts of school closures. Looking ahead, the expected change of hurricane frequency and intensity under climate change makes such systematic data compilation an especially critical resource for both public and academic use. 

Dataset and code for the following paper: Abbasi, D., Safari, S., Nateghi, R., & Reilly, A. C. (2025). Learning after the Storm: Characterizing and Understanding Prolonged Unplanned School Closures after Hurricanes. International Journal of Disaster Risk Reduction, 105611. Schools are vital for providing both education and social services, but when closures extend for long periods due to disasters, they can disrupt student learning and cause widespread negative consequences for families and the broader community. This dataset compiles information on Prolonged Unplanned School Closures (PUSCs)—those lasting seven or more unexpected days—linked to hurricanes from the 2011/12 to 2018/19 school years across East and Gulf Coast school districts. It includes data on districts that closed, as well as counterfactuals where closures were avoided or brief. Supplementary district-level data cover socioeconomic factors, geography, school district capacity, and hazard characteristics, along with code used for analysis. This dataset (CSV and XLSX) and code underpin the study “Learning after the Storm: Characterizing and Understanding Prolonged Unplanned School Closures After Hurricanes.”