Dataset from Tracking the COVID-19 Epidemic in Sewage (TRACES)

Background: The purpose of this study was to optimize wastewater-based testing (WBT) strategies for cost-effective surveillance and transmission tracking of SARS-CoV-2 in a complex urban environment. Wastewater testing offered an efficient approach to monitor community-level infection trends, yet optimal sampling modalities and protocols remained unclear. The study leveraged a diverse inner-city university campus including undergraduate and postgraduate dormitories, research facilities, and medical buildings to refine and evaluate methods for detecting and modeling SARS-CoV-2 presence in wastewater.

Materials/Methods: This study optimized WBT surveillance strategies by sampling waste streams at multiple levels, including individual buildings, surrounding sewersheds, and centralized wastewater treatment plants. Normalized wastewater data were used to model COVID-19 case counts and assess the predictive capacity of WBT for identifying infection trends. Metatranscriptomic analyses were conducted to monitor circulating and emerging SARS-CoV-2 variants within wastewater samples. Additionally, the study developed and tested point-of-use microfluidics systems to enhance the timeliness and accessibility of wastewater testing. The combined approach integrated molecular, engineering, and computational methods to identify the most effective protocols for large-scale, real-time surveillance of viral transmission.

Outcome/Impact: This study advanced the field of wastewater-based epidemiology by improving understanding of optimal sampling strategies and the relationship between wastewater viral load and community infection rates. The integration of metatranscriptomic sequencing allowed for early detection of variant emergence, while the development of portable microfluidic systems increased the feasibility of rapid on-site testing. The findings demonstrated the potential of wastewater surveillance as a scalable, cost-effective public health tool for monitoring and mitigating future infectious disease outbreaks.