PDF(Pubmed)
Abstract：
The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring the SARS-CoV-2 prevalence in a city in northern Italy from October 2021 to May 2023. Based on a previously used deterministic model, this study proposed a variation to account for the population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated using healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred during the period considered, demonstrating the ability of the model to predict the relevant fluctuations in the number of cases. The population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied to compare the virus load values across cities with different population demographics and sewer network structures, improving the comparability of the WBE data for effective surveillance and intervention strategies.
摘要：
该研究调查了从2021年10月至2023年5月，基于废水的流行病学（WBE）作为监测意大利北部城市SARS-CoV-2流行的工具的应用。基于以前使用的确定性模型，这项研究提出了一个变异来解释下水道网络中的种群特征和病毒生物降解。该模型计算了城市不同地区一段时间内的病毒载量和相应的COVID-19病例，并使用医疗保健数据进行了验证，同时考虑了病毒突变，疫苗接种,和测试可变性。在考虑期间发生的三个波中，预测病例和报告病例之间的相关性很高，证明模型预测案例数量相关波动的能力。人群特征对预测和报告的感染率没有实质性影响。相反，生物降解显著降低了到达污水处理厂的病毒载量，导致研究区域产生的总病毒载量减少30%。这种方法可以应用于比较不同人口统计和下水道网络结构的不同城市的病毒载量值，提高WBE数据的可比性，以实现有效的监测和干预策略。
