CAREER: Wastewater Counts: Real-time de facto Population Estimation for Quantitative Wastewater-based Epidemiology

Washington University, Saint Louis MO

Investigators

Abstract

Wastewater-based epidemiology (WBE) has emerged as a complementary approach to existing clinical tools to track the spread of infectious disease. WBE is based on using microbial biomarkers in wastewater to monitor the onset, spread, and community transmission of infectious diseases. Although WBE has provided valuable insight into the spread of SARS-CoV-2 virus during the COVID-19 pandemic, much work remains to be done to enable accurate quantitative estimates using this technique. The goal of this CAREER project is to address this critical challenge through the development of computational approaches, models, and tools to accurately predict the size of a disease outbreak from wastewater biomarker data. Successful completion of this project will benefit society through the development of new and experimentally validated computational tools to predict community disease spread. This will allow a fuller exploitation of the large amount of WBE data that are being collected in the United States to advance public health. Further benefits to society will be achieved through the mentoring of a doctoral student at Washington University in St. Louis. Additional benefits derive from the development of an education kit focused on environmental data sciences to advance science literacy in K-12 students. The overarching goal of this CAREER project is to advance the science and engineering of wastewater-based epidemiology (WBE) through the development and validation of new computational tools to estimate the size of affected population in real time from biomarkers in untreated wastewater. This will be achieved through specific research designed to (1) build a computational framework for wastewater microbiome-based population models, (2) develop and experimentally validate models and computational tools for estimating the size affected populations in infectious disease outbreaks using community wastewater surveillance data, and (3) apply these new models and tools to evaluate and improve the design of WBE sampling programs. The educational plan will (1) engage wastewater treatment and public health practitioners in refining and disseminating microbiome-based population models and design tools for WBE, 2) enhance the interdisciplinary training of environmental engineering undergraduate and graduate students by integrating data science into the educational curriculum, and 3) develop and distribute a K-12 educational kit on environmental data science based on Next Generation Science Standards. The successful completion of this project has strong potential to transform our ability to track disease outbreaks through the development of new computational tools for WBE surveillance programs. The broader impacts of this project will be enhanced by training practitioners and providing educational resources to diverse student populations at the K-12, college, and postgraduate levels. 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.