Department of Biological Engineering, Massachusetts Institute of Technology, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, USA.
Biobot Analytics, Inc., Cambridge, MA, USA.
Sci Total Environ. 2022 Jan 20;805:150121. doi: 10.1016/j.scitotenv.2021.150121. Epub 2021 Sep 4.
Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.
目前对 COVID-19 流行率的估计主要基于有症状的临床诊断病例。大量未确诊感染的存在阻碍了对病毒传播的全人群调查。在这里,我们在马萨诸塞州的一个主要城市污水处理设施中,从 2020 年 1 月初到 5 月定量检测了废水中 SARS-CoV-2 的浓度并追踪其动态。3 月 3 日首次在废水中检测到 SARS-CoV-2。废水中的 SARS-CoV-2 RNA 浓度与临床诊断的新 COVID-19 病例相关,其趋势比临床数据早出现 4-10 天。我们通过将回溯的新临床病例与平均人群水平的病毒脱落功能进行卷积,来推断病毒脱落动力学。推断的病毒脱落功能显示出早期峰值,可能在症状出现和临床诊断之前,与新出现的临床和实验证据一致。这一发现表明,废水中 SARS-CoV-2 的浓度可能主要由感染早期的病毒脱落驱动。这项工作表明,纵向的废水分析可以用于在临床报告之前提前识别疾病传播趋势,并推断新感染个体的早期病毒脱落动态,这在临床研究中很难捕捉到。