Fu Songzhe, Zhang Yixiang, Wang Rui, Deng Zhiqiang, He Fenglan, Jiang Xiaotong, Shen Lixin
Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences, Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China.
Water Res. 2023 Dec 1;247:120751. doi: 10.1016/j.watres.2023.120751. Epub 2023 Oct 19.
Wastewater-based epidemiology (WBE) is a promising tool for monitoring the spread of SARS-CoV-2 and other pathogens, providing a novel public health strategy to combat disease. In this study, we first analysed nationwide reports of infectious diseases and selected Salmonella, norovirus, and influenza A virus (IAV) as prioritized targets apart from SARS-CoV-2 for wastewater surveillance. Next, the decay rates of Salmonella, norovirus, and IAV in wastewater at various temperatures were established to obtain corrected pathogen concentrations in sewage. We then monitored the concentrations of these pathogens in wastewater treatment plant (WWTP) influents in three cities, establishing a prediction model to estimate the number of infected individuals based on the mass balance between total viral load in sewage and individual viral shedding. From October 2022 to March 2023, we conducted multipathogen wastewater surveillance (MPWS) in a WWTP serving one million people in Xi'an City, monitoring the concentration dynamics of SARS-CoV-2, Salmonella, norovirus, and IAV in sewage. The infection peaks of each pathogen were different, with Salmonella cases and sewage concentration declining from October to December 2022 and only occasionally detected thereafter. The SARS-CoV-2 concentration rapidly increased from December 5th, peaked on December 26th, and then quickly decreased until the end of the study. Norovirus and IAV were detected in wastewater from January to March 2023, peaking in February and March, respectively. We used the prediction models to estimate the rate of SARS-CoV-2 infection in Xi'an city, with nearly 90 % of the population infected in urban regions. There was no significant difference between the predicted and actual number of hospital admissions for IAV. We also accurately predicted the number of norovirus cases relative to the reported cases. Our findings highlight the importance of wastewater surveillance in addressing public health priorities, underscoring the need for a novel workflow that links the prediction results of populations with public health interventions and allocation of medical resources at the community level. This approach would prevent medical resource panic squeezes, reduce the severity and mortality of patients, and enhance overall public health outcomes.
基于废水的流行病学（WBE）是监测新冠病毒（SARS-CoV-2）和其他病原体传播的一种很有前景的工具，为抗击疾病提供了一种全新的公共卫生策略。在本研究中，我们首先分析了全国传染病报告，并选择沙门氏菌、诺如病毒和甲型流感病毒（IAV）作为除SARS-CoV-2之外用于废水监测的优先目标。接下来，确定了沙门氏菌、诺如病毒和IAV在不同温度下于废水中的衰减率，以获取污水中经校正的病原体浓度。然后，我们监测了三个城市污水处理厂（WWTP）进水口这些病原体的浓度，建立了一个预测模型，以便根据污水中病毒总载量与个体病毒排出量之间的质量平衡来估算感染个体数量。2022年10月至2023年3月，我们在西安市一座服务百万人的污水处理厂开展了多病原体废水监测（MPWS），监测污水中SARS-CoV-2、沙门氏菌、诺如病毒和IAV的浓度动态。每种病原体的感染高峰各不相同，沙门氏菌病例及污水浓度在2022年10月至12月期间下降，此后仅偶尔检测到。SARS-CoV-2浓度从12月5日迅速上升，于12月26日达到峰值，然后迅速下降直至研究结束。诺如病毒和IAV在2023年1月至3月的废水中被检测到，分别在2月和3月达到峰值。我们使用预测模型估算了西安市的SARS-CoV-2感染率，城市地区近90%的人口被感染。IAV的预测住院人数与实际住院人数之间没有显著差异。我们还相对于报告病例准确预测了诺如病毒病例数。我们的研究结果凸显了废水监测在解决公共卫生优先事项方面的重要性，强调需要一种将人群预测结果与公共卫生干预措施以及社区层面医疗资源分配相联系的全新工作流程。这种方法将防止医疗资源恐慌性挤兑，降低患者的严重程度和死亡率，并提高整体公共卫生结果。
