Wastewater-based surveillance on metagenomics: progress, perspectives, and practical applications

Wastewater-based surveillance on metagenomics is moving beyond pathogen and antimicrobial resistance detection. Currently, from a single wastewater sample, multiple public health signals can be simultaneously retrieved, including human, animal, and plant pathogens, antimicrobial resistance genes, mobile genetic elements, virulence factors, the gut microbiome, host-derived DNA/RNA, and other gene signals related to human activities and exposure. These signals can reflect biological population distribution, infections in humans, animals and plants, population diet and health, as well as the epidemiological dynamics of antimicrobial resistance. However, the true potential lies in integrating wastewater metagenomic data with wastewater chemical multimodal data and other multi-source data—such as demographic and socioeconomic data, public health survey data, clinical case reports, meteorological data, etc. Such multi-source integration helps improve the accuracy of signal interpretation and enhances the depth and breadth of urban health situational awareness.

Dr. Xialu Lin is working at the Xiamen Center for Disease Control and Prevention and leading the Wastewater-Based Surveillance (WBS) project in Xiamen, China. Her research integrates chemical and microbial wastewater surveillance to uncover hidden public health intelligence and develops scalable workflow tools for data-driven decision-making.