Researchers have created a mathematical model designed to help identify which neighborhoods should be prioritized for search and rescue operations after a hurricane. This tool aims to help the Coast Guard and other emergency responders act more efficiently during the critical first 48 to 72 hours following a disaster. The study was published in the International Journal of Disaster Risk Reduction. "During the first 48 hours of a major disaster, responders come from all over the country, but they often work with very limited information," says Brandon McConnell, co-author of the study and an associate research professor at North Carolina State University. "Our goal was to build a model that could predict where the greatest rescue needs would be, helping guide planning efforts." The model identifies census tracts—specific geographic areas defined by the U.S. Census Bureau—where residents are most likely to need rescue. While responders will eventually check every area, the model helps them focus on those most likely to have people in need. The researchers used data on factors that increase vulnerability during hurricanes, such as physical disabilities and limited financial resources. They combined this with U.S. Census data and National Flood Insurance Program data to identify areas where people may struggle to evacuate and regions at higher risk of flooding. The research was also influenced by the real-world experience of Patrick Leavitt, the study’s first author and an active-duty Coast Guard officer. His firsthand knowledge of emergency response operations helped shape the model’s design. To test the model, the researchers applied it to Hurricane Harvey, a powerful Category 4 storm that hit Texas in 2017 and caused severe flooding in Houston. By comparing their model’s predictions with actual rescue locations, they found that the framework was effective, though not perfect. They believe it can be improved with better data and is already useful for responders. The model can be run quickly, providing real-time guidance to emergency teams as they deploy. It can also help in planning for future disasters. Patrick Leavitt notes that the tool is valuable not just during the response phase but also in preparing for emergencies. The researchers are open to working with emergency management officials to refine the model and make it more practical for use in real-world situations.