Flooding poses major threats to communities across the United States, especially in areas with older or inadequate stormwater systems. These floods can damage homes, contaminate drinking water, cause sewage overflows, and expose people to harmful health threats. To help address these dangers, this project will collect detailed, neighborhood-level data for building new understanding about how repeated floods affect human well-being. By combining community input with data on flooding, environmental microbes, and health outcomes, the research team will develop new ways of predicting which areas face the highest risks. The findings will be used to help residents and decision-makers identify and reduce flood-related health dangers in their communities. The project will also broaden use of the new methods and tools by providing training to help other researchers conduct related work. This research integrates expertise from anthropology, hydrology, microbiology, environmental engineering, and data science. The research team will create a comprehensive dataset linking flood frequency, pathogen presence in water and soil, resident lived experiences, and gastrointestinal infection rates in communities. Using these data, they will conduct geospatial analyses to examine links between flooding, pathogen levels, and infection risk. The research team will then apply advanced Bayesian models to the dataset to predict how flooding influences infection risk over time and across different lo