eMB: Collaborative Research: Integrated Hybrid Mathematical Modeling for Schistosomiasis Elimination

This project is a collaboration amongst the University of Florida (Gainesville), the University of Georgia (Athens), and the University of Massachusetts (Amherst). Schistosomiasis, a disease caused by parasitic worms and transmitted through contact with contaminated freshwater, poses a significant public health threat in many developing regions. Hence, designing effective intervention strategies to mitigate the disease’s impact is timely and critical. This project aims to advance our understanding of schistosomiasis transmission dynamics and control. Specifically focusing on schistosomiasis in Zanzibar and Ethiopia, this research will create and use innovative mathematical modeling tools to understand how various factors like human movement and environmental changes influence disease transmission. This will help to identify the best strategies to control and eventually eliminate schistosomiasis as a public health problem. The project is not only scientifically important but also has significant public health, educational, and societal implications. The educational and societal impacts include training a diverse group of students (including students from underrepresented groups) and fostering interdisciplinary and collaborative research skills. The project will provide novel analytic tools for efficient resource management and inform evidence-based policies for sustainable elimination of schistosomiasis, thereby significantly impacting global health. A workshop in Zanzibar will further help building workforce in quantitative public health and disseminating scientific knowledge. The proposed project seeks to develop advanced mathematical models to improve our understanding and management of schistosomiasis transmission dynamics, especially during the transition from high to low transmission phases towards elimination. Current models often fail to adequately capture low transmission environments, where random events, spatial and temporal heterogeneities, as well as environmental factors significantly impact transmission persistence. The project aims to develop a novel and robust hybrid deterministic-agent-based modeling framework integrating snail population dynamics (an aspect hither to overlooked in many schistosomiases transmission models) and environmental factors, using data for Schistosoma haematobium from Zanzibar and Schistosoma mansoni from Ethiopia. This innovative dual-phase framework will capture complexities in both high and low transmission settings, incorporating human movement, hydrological networks, and parasite gene flow. The project will assess persistence drivers under low-level transmission, identify transmission breakpoints, and optimize intervention strategies, offering new insights into transmission dynamics and control strategies that lead to impactful public health policies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.