Microplastics, the persistent pollutants already known to threaten ecosystems and human health, have a previously unrecognized dark side inside the world's urban sewer networks.

Genomic surveillance — the process of monitoring and sequencing pathogens — is one of the most important tools for detecting emerging viral threats. But global surveillance systems remain costly, unevenly distributed and often are too slow to identify dangerous variants before they spread internationally,  amplifying future threats of disease outbreaks.

A recently published research paper in Nature Communications, co-authored by Dr. Patricia Ning, assistant statistics professor, and Jifan Li, a doctoral candidate in the Department of Statistics, along with collaborators from multiple international institutions, introduces a new framework to rectify these issues while using fewer resources, making genomic surveillance rapid and cost-effective in preparation for new strains of COVID-19.