School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia.
Urban utilities, Brisbane, Queensland, Australia.
J Hazard Mater. 2022 Jun 15;432:128667. doi: 10.1016/j.jhazmat.2022.128667. Epub 2022 Mar 10.
Wastewater-based epidemiology (WBE) approach for COVID-19 surveillance is largely based on the assumption of SARS-CoV-2 RNA shedding into sewers by infected individuals. Recent studies found that SARS-CoV-2 RNA concentration in wastewater (C) could not be accounted by the fecal shedding alone. This study aimed to determine potential major shedding sources based on literature data of C, along with the COVID-19 prevalence in the catchment area through a systematic literature review. Theoretical C under a certain prevalence was estimated using Monte Carlo simulations, with eight scenarios accommodating feces alone, and both feces and sputum as shedding sources. With feces alone, none of the WBE data was in the confidence interval of theoretical C estimated with the mean feces shedding magnitude and probability, and 63% of C in WBE reports were higher than the maximum theoretical concentration. With both sputum and feces, 91% of the WBE data were below the simulated maximum C in wastewater. The inclusion of sputum as a major shedding source led to more comparable theoretical C to the literature WBE data. Sputum discharging behavior of patients also resulted in great fluctuations of C under a certain prevalence. Thus, sputum is a potential critical shedding source for COVID-19 WBE surveillance.
基于污水的流行病学(WBE)方法用于 COVID-19 监测,主要基于假设受感染个体将 SARS-CoV-2 RNA 排入污水。最近的研究发现,污水中的 SARS-CoV-2 RNA 浓度(C)不能仅用粪便排出物来解释。本研究旨在通过系统文献回顾,根据 C 的文献数据以及集水区内 COVID-19 的流行情况,确定潜在的主要排出源。通过蒙特卡罗模拟,使用八种情况分别单独考虑粪便和痰液作为排出源,估计了特定流行率下的理论 C。仅用粪便,没有一个 WBE 数据处于用平均粪便排出量和概率估计的理论 C 的置信区间内,并且 63%的 WBE 报告中的 C 高于理论最大浓度。同时考虑痰液和粪便时,91%的 WBE 数据低于污水中模拟的最大理论 C。将痰液作为主要排出源包括在内,使理论 C 与文献中的 WBE 数据更具可比性。患者的痰液排出行为也导致了在一定流行率下 C 的巨大波动。因此,痰液是 COVID-19 WBE 监测的一个潜在重要排出源。