ArticleFrontiers in microbiology2026
Wastewater-based surveillance and early warning-forecasting framework for norovirus: a two-year longitudinal study in Shenzhen, China.
Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: Norovirus (NoV) is a leading cause of acute gastroenteritis globally; however, traditional clinical surveillance underestimates its true infection burden. Wastewater-based epidemiology (WBE) offers a novel approach for comprehensive viral monitoring. This study aimed to develop and validate a practical WBE framework integrating a two-tiered early warning system and trend forecasting to support public health interventions against NoV. Methods: A two-year (August 2022-August 2024) WBE study was conducted in Shenzhen. NoV in influent wastewater samples from five wastewater treatment plants was monitored using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). We employed a clinical data-calibrated approach to derive estimates of NoV cases from reported infectious diarrhea data; these estimates served as the gold standard. Using this gold standard, we employed the Moving Epidemic Method (MEM) to establish and validate a two-tiered early warning system based on wastewater NoV concentrations. In addition, we developed a Poisson regression model (PRM) to forecast NoV infection trends. Results: Wastewater NoV loads exhibited distinct seasonal fluctuations. The clinical data-calibrated estimates correlated strongly with wastewater viral concentrations ( Conclusion: WBE monitoring effectively captures the seasonal fluctuations of NoV infections in the population. This study provides a practical WBE framework integrating a two-tiered early warning system with one-week-ahead trend forecasting, thereby enabling the transformation of passive monitoring into an actionable public health tool for NoV.
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