Publication date: May 20, 2025

As COVID-19 shifts toward endemicity, ongoing surveillance remains critical to identifying and containing potential outbreaks, particularly in high-risk settings. Wastewater monitoring at targeted institutions offers a promising approach for early detection; however, its utility in forecasting broader epidemic trends remains underexplored. This study aimed to establish the wastewater surveillance platform for SARS-CoV-2 in a University Hospital to forecast the epidemic at the hospital, the surrounding community, and the city levels. During April and October 2022, we conducted routine wastewater sampling at seven sampling wells across the campus twice weekly. The direct viral RNA capture method was adopted for the pretreatment, concentration, and extraction of viral RNA. The presence of SARS-CoV-2 RNA in the wastewater samples was detected and quantified with RT-qPCR targeting N1, N2, and E-gene. SARS-CoV-2 signals relative to pepper mild mottle virus were calculated. Simple linear regression models were used to model the future moving averages of cumulative confirmed cases per 100,000 population at the hospital, community, and city levels. High consistency was observed in the E, N1, and N2 gene targets. Even with only eight new cases in the Zhongzheng District (5. 42 per 100,000 population) and 145 cases in the entire city (5. 85 per 100,000 population), the virus can be detected in sewage, indicating promising sensitivity. The relative viral signals in the wastewater were strongly associated with future epidemiological indicators at the hospital, community, and city levels. Wastewater sampling and quantification of SARS-CoV-2 is proven to be an efficient and robust method for the tracking and forecasting of infection trends within and beyond hospital settings.

Semantics

Original Article