Since many infected people experience no or few symptoms, the SARS-CoV-2 epidemic is frequently monitored through massive virus testing of the population, an approach that may be biased and may be difficult to sustain in low-income countries. Since SARS-CoV-2 RNA can be detected in stool samples, quantifying SARS-CoV-2 genome by RT-qPCR in wastewater treatment plants (WWTPs) has been carried out as a complementary tool to monitor virus circulation among human populations. However, measuring SARS-CoV-2 viral load in WWTPs can be affected by many experimental and environmental factors. To circumvent these limits, we propose here a novel indicator, the wastewater indicator (WWI), that partly reduces and corrects the noise associated with the SARS-CoV-2 genome quantification in wastewater (average noise reduction of 19%). All data processing results in an average correlation gain of 18% with the incidence rate. The WWI can take into account the censorship linked to the limit of quantification (LOQ), allows the automatic detection of outliers to be integrated into the smoothing algorithm, estimates the average measurement error committed on the samples and proposes a solution for inter-laboratory normalization in the absence of inter-laboratory assays (ILA). This method has been successfully applied in the context of Obépine, a French national network that has been quantifying SARS-CoV-2 genome in a representative sample of French WWTPs since March 5th 2020. By August 26th, 2021, 168 WWTPs were monitored in the French metropolitan and overseas territories of France. We detail the process of elaboration of this indicator, show that it is strongly correlated to the incidence rate and that the optimal time lag between these two signals is only a few days, making our indicator an efficient complement to the incidence rate. This alternative approach may be especially important to evaluate SARS-CoV-2 dynamics in human populations when the testing rate is low.

由于许多感染者没有或很少出现症状，因此经常通过对人群进行大规模病毒检测来监测 SARS-CoV-2 疫情，这种方法可能存在偏见，并且在低收入国家可能难以维持。由于可以在粪便样本中检测到 SARS-CoV-2 RNA，因此在废水处理厂 (WWTP) 中通过 RT-qPCR 定量 SARS-CoV-2 基因组已作为监测人群中病毒传播的补充工具。然而，测量污水处理厂中的 SARS-CoV-2 病毒载量可能会受到许多实验和环境因素的影响。为了规避这些限制，我们在这里提出了一种新的指标，即废水指标 (WWI)，它可以部分减少和纠正与废水中 SARS-CoV-2 基因组定量相关的噪音（平均噪音降低 19%）。所有数据处理的结果是与发病率的平均相关增益为 18%。WWI 可以考虑与定量限 (LOQ) 相关的审查制度，允许将异常值的自动检测集成到平滑算法中，估计样本上的平均测量误差，并提出实验室间标准化的解决方案在没有实验室间分析（ILA）的情况下。该方法已成功应用于法国国家网络 Obépine，该网络自 2020 年 3 月 5 日起一直在法国污水处理厂代表性样本中量化 SARS-CoV-2 基因组。截至 2021 年 8 月 26 日，法国国家网络中的 168 个污水处理厂受到监测。法国本土和法国海外领土。我们详细介绍了该指标的制定过程，表明它与发病率密切相关，并且这两个信号之间的最佳时间间隔只有几天，使我们的指标成为发病率的有效补充。当检测率较低时，这种替代方法对于评估人群中 SARS-CoV-2 的动态可能特别重要。