Li Xuan, Zhang Shuxin, Shi Jiahua, Luby Stephen P, Jiang Guangming
School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia.
Woods Institute for the Environment, Stanford University, United States.
Chem Eng J. 2021 Jul 1;415:129039. doi: 10.1016/j.cej.2021.129039. Epub 2021 Feb 20.
Wastewater-based epidemiology (WBE) is a promising approach for estimating population-wide COVID-19 prevalence through detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. However, various methodological challenges associated with WBE would affect the accuracy of prevalence estimation. To date, the overall uncertainty of WBE and the impact of each step on the prevalence estimation are largely unknown. This study divided the WBE approach into five steps (i.e., virus shedding; in-sewer transportation; sampling and storage; analysis of SARS-CoV-2 RNA concentration in wastewater; back-estimation) and further summarized and quantified the uncertainties associated with each step through a systematic review. Although the shedding of SARS-CoV-2 RNA varied greatly between COVID-19 positive patients, with more than 10 infected persons in the catchment area, the uncertainty caused by the excretion rate became limited for the prevalence estimation. Using a high-frequency flow-proportional sampling and estimating the prevalence through actual water usage data significantly reduced the overall uncertainties to around 20-40% (relative standard deviation, RSD). And under such a scenario, the analytical uncertainty of SARS-CoV-2 RNA in wastewater was the dominant factor. This highlights the importance of using surrogate viruses as internal or external standards during the wastewater analysis, and the need for further improvement on analytical approaches to minimize the analytical uncertainty. This study supports the application of WBE as a complementary surveillance strategy for monitoring COVID-19 prevalence and provides methodological improvements and suggestions to enhance the reliability for future studies.
基于废水的流行病学（WBE）是一种很有前景的方法，可通过检测废水中的严重急性呼吸综合征冠状病毒2（SARS-CoV-2）RNA来估计全人群的新冠病毒感染率。然而，与WBE相关的各种方法学挑战会影响感染率估计的准确性。迄今为止，WBE的总体不确定性以及每个步骤对感染率估计的影响在很大程度上尚不清楚。本研究将WBE方法分为五个步骤（即病毒排放；下水道内传输；采样与储存；废水中SARS-CoV-2 RNA浓度分析；反向估计），并通过系统综述进一步总结和量化了与每个步骤相关的不确定性。尽管SARS-CoV-2 RNA在新冠病毒阳性患者之间的排放量差异很大，但在集水区有超过10名感染者的情况下，排泄率导致的不确定性对感染率估计的影响变得有限。采用高频流量比例采样并通过实际用水数据估计感染率，可将总体不确定性显著降低至20%-40%左右（相对标准偏差，RSD）。在这种情况下，废水中SARS-CoV-2 RNA的分析不确定性是主导因素。这凸显了在废水分析过程中使用替代病毒作为内部或外部标准的重要性，以及进一步改进分析方法以最小化分析不确定性的必要性。本研究支持将WBE作为监测新冠病毒感染率的补充监测策略加以应用，并为提高未来研究的可靠性提供了方法改进和建议。
