Wastewater-Based Epidemiology is a new tool that can provide a complementary approach to current infectious disease surveillance and an early warning system for disease outbreaks. Rapid advances in high-throughput sequencing technologies have decreased sequencing costs and thus revolutionized disease surveillance. In this project, we will explore the total pooled metagenome from wastewater treatment plants, as a trusted source reflecting community-level population health data. We will evaluate the association between the health records in a given locality and the corresponding wastewater metagenomic signatures. This project aims to identify disease risk indicators using bioinformatics and data science, including machine learning. Furthermore, the research produces a cost-effective community-level method to generate health information for infection epidemiology and population health research.

2023

2027