Mapping Flood Exposure Pathways: Applications of Downscaling for Giardiasis Surveillance

The increasing frequency and intensity of storm events have heightened concerns about their impact on public health, particularly infectious diseases like giardiasis, which are often associated with flooding. This study employs aspects of Thacker’s public health surveillance framework, focusing on hazard and exposure surveillance, to identify potential pathways for disease transmission during and after flooding events. By incorporating environmental modeling and downscaling state-level disease data into the Hazard-Exposure-Outcome Axis framework, this methodology enables a systematic assessment of flooding hazards and exposure risks. The goal is to map storm events, flooding exposure, and vulnerable populations to better understand the mechanisms driving giardia transmission in high-risk areas. Storm event data from the National Oceanic and Atmospheric Administration (NOAA) Storm Events Database and flooding exposure data are analyzed to identify the environmental pathway between flooding and contextual factors such as proximity to recreational areas and at-risk behaviors. The host component is then incorporated with population data to identify areas with vulnerable populations. Given the aggregation of disease data at the state level, giardiasis surveillance data from the Centers for Disease Control and Prevention’s (CDC) National Notifiable Diseases Surveillance System (NNDSS) will be downscaled to finer geographic levels. Geographic Information Systems (GIS) and computational techniques will be utilized throughout to spatially redistribute exposure and population data, refine the identification of flood-related risk zones, and prioritize targeted interventions for at-risk populations at finer geographies. This study aims to provide a framework for understanding giardiasis outbreak risk and improving public health responses by actionable information for public health. Further, findings will improve preparedness through actionable risk maps, integrating environmental hazards and population dynamics to enhance early-warning systems and preventive measures in flood-prone areas.