Mining of wastewater metagenomic data to identify population health and disease trends

Wastewater-Based Epidemiology is a new epidemiological tool that can provide a complementary approach to current infectious disease surveillance and an early warning system for disease outbreaks. Continuous advances in high-throughput sequencing technologies have decreased sequencing costs revolutionizing disease surveillance.

In this project, we will explore total metagenome from wastewater treatment plants, which are a trusted source of community-level population health data. We evaluate the correlation between the health records in a given locality and the corresponding wastewater metagenomic signatures. The project aims to identify disease risk indicators using bioinformatics and data science, including machine learning.

Furthermore, the research produces a cost-effective community-level alternative to generating health information for infection epidemiology and population health research.