A Predictive Framework for Human Infection Risk: Genomic Characterization of Vibrio spp. in the Context of Algal Blooms and Extreme Weather Events

About This Grant

Summary Pathogenic Vibrio spp., including V. vulnificus, V. parahaemolyticus, and V. alginolyticus, are naturally occurring seawater bacteria that pose a growing threat to public health, particularly in coastal regions of the United States. These organisms are highly sensitive to geophysical conditions such as sea surface temperature, salinity, and nutrient availability—factors increasingly influenced by ecological changes and extreme weather events. Florida, with its extensive coastline and frequent exposure to hurricanes and harmful algal blooms (HABs), reports the highest incidence of vibriosis in the nation. This project aims to develop a predictive, satellite-based public health forecasting system—VIGOR (Vibrio Infection Genomics for Outbreak Risk Forecasting)—to identify and monitor high-risk zones for Vibrio spp. proliferation. The long-term objective is to reduce the burden of waterborne infections by enabling early detection and targeted interventions. The specific aims are: (1) to detect and characterize pathogenic Vibrio spp. in coastal water microbiomes using molecular and genomic tools; (2) to determine the impact of severe weather events and geophysical parameters on prevalence and genomic diversity of pathogenic Vibrio spp; and (3) to develop and validate ecological niche models (ENMs), particularly using MaxEnt architechture, to forecast seasonal and spatial hotspots of Vibrio spp. risk for human populations. The research design integrates biweekly field sampling, high-throughput sequencing, satellite remote sensing, and machine learning-based pathogen modeling, and develop a platform for real-time public health information dissemination. Environmental and microbial data will be used to train and validate predictive models, which will be overlaid with demographic and infrastructural vulnerability indicators to inform public health decision-making. This work aligns with NIAID’s mission by advancing predictive capabilities for environment-sensitive infectious diseases and supporting proactive, data-driven public health responses.