Abstract：
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.
摘要：
基于废水的流行病学（WBE）是监测SARS-CoV-2和其他病原体传播的有前途的工具，提供一种新的公共卫生策略来对抗疾病。在这项研究中,我们首先分析了全国的传染病报告，并选择了沙门氏菌，诺如病毒,和甲型流感病毒（IAV）作为除SARS-CoV-2外的优先目标用于废水监测。接下来,沙门氏菌的腐烂率，诺如病毒,建立了各种温度下废水中的IAV和IAV，以获得污水中经过校正的病原体浓度。然后，我们监测了三个城市污水处理厂（WWTP）进水中这些病原体的浓度，建立预测模型，根据污水中总病毒载量和个体病毒脱落之间的质量平衡来估计感染个体的数量。从2022年10月到2023年3月，我们在为西安市100万人提供服务的污水处理厂中进行了多病原体废水监测（MPWS）。监测SARS-CoV-2、沙门氏菌、诺如病毒,和IAV在污水中。每种病原体的感染峰值不同，从2022年10月到12月，沙门氏菌病例和污水浓度下降，此后仅偶尔检测到。SARS-CoV-2浓度从12月5日起迅速上升,12月26日达到顶峰,然后迅速下降，直到研究结束。2023年1月至3月在废水中检测出诺如病毒和IAV，2月和3月达到峰值，分别。我们使用预测模型来估计西安市SARS-CoV-2的感染率，近90%的人口在城市地区感染。IAV住院的预测和实际人数之间没有显着差异。我们还准确预测了诺如病毒病例相对于报告病例的数量。我们的发现强调了废水监测在解决公共卫生优先事项方面的重要性。强调需要一种新颖的工作流程，将人群的预测结果与社区一级的公共卫生干预措施和医疗资源分配联系起来。这种方法可以防止医疗资源恐慌，降低患者的严重程度和死亡率，并提高整体公共卫生结果。
