Wu Fuqing, Zhang Jianbo, Xiao Amy, Gu Xiaoqiong, Lee Wei Lin, Armas Federica, Kauffman Kathryn, Hanage William, Matus Mariana, Ghaeli Newsha, Endo Noriko, Duvallet Claire, Poyet Mathilde, Moniz Katya, Washburne Alex D, Erickson Timothy B, Chai Peter R, Thompson Janelle, Alm Eric J
Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
mSystems. 2020 Jul 21;5(4):e00614-20. doi: 10.1128/mSystems.00614-20.
Wastewater surveillance represents a complementary approach to clinical surveillance to measure the presence and prevalence of emerging infectious diseases like the novel coronavirus SARS-CoV-2. This innovative data source can improve the precision of epidemiological modeling to understand the penetrance of SARS-CoV-2 in specific vulnerable communities. Here, we tested wastewater collected at a major urban treatment facility in Massachusetts and detected SARS-CoV-2 RNA from the gene at significant titers (57 to 303 copies per ml of sewage) in the period from 18 to 25 March 2020 using RT-qPCR. We validated detection of SARS-CoV-2 by Sanger sequencing the PCR product from the gene. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of 25 March. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks. Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is orders of magnitude greater than the number of confirmed clinical cases and therefore may significantly impact efforts to understand the case fatality rate and progression of disease. These data may help inform decisions surrounding the advancement or scale-back of social distancing and quarantine efforts based on dynamic wastewater catchment-level estimations of prevalence.
废水监测是临床监测的一种补充方法,用于检测新型冠状病毒SARS-CoV-2等新兴传染病的存在和流行情况。这种创新的数据源可以提高流行病学建模的精度,以了解SARS-CoV-2在特定脆弱社区的渗透情况。在此,我们对马萨诸塞州一家主要城市污水处理设施收集的废水进行了检测,并于2020年3月18日至25日期间,使用逆转录定量聚合酶链反应(RT-qPCR)从基因中检测到了具有显著滴度(每毫升污水57至303个拷贝)的SARS-CoV-2核糖核酸(RNA)。我们通过对来自该基因的聚合酶链反应(PCR)产物进行桑格测序,验证了SARS-CoV-2的检测。截至3月25日,观察到的病毒滴度显著高于基于马萨诸塞州临床确诊病例预期的滴度。我们的方法具有可扩展性,可能有助于对SARS-CoV-2大流行及未来疫情进行建模。基于废水的监测是一种很有前景的主动疫情监测方法。SARS-CoV-2在临床病程早期就会从粪便中排出,并感染大量无症状人群,使其成为基于废水监测的理想目标。在本研究中,我们制定了一项实验室方案,通过定量聚合酶链反应(qPCR)分析来量化原污水中的病毒滴度,并用测序分析验证结果。我们的结果表明,根据废水病毒滴度估计的阳性病例数比确诊临床病例数高出几个数量级,因此可能会对了解病死率和疾病进展的努力产生重大影响。这些数据可能有助于根据动态废水集水区水平的流行率估计,为围绕社会距离和隔离措施的推进或缩减做出决策提供信息。