Collaborative Research: RAPID: Wastewater Informed Epidemiological Monitoring of SARS-CoV-2

合作研究：RAPID：废水知情的 SARS-CoV-2 流行病学监测

• 批准号: 2027758
• 负责人: Joe Brown
• 金额: $ 4.55万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2027758&HistoricalAwards=false
• 关键词: Collaborative; Research; RAPID; Wastewater; Informed

The global COVID-19 pandemic causing considerable human health and economic impacts presents the research community with a unique set of challenges that must be addressed in real time. Critical to managing any pandemic is the accurate estimation of how many people are infected within communities. SARS-CoV-2, the virus causing COVID-19, is excreted in the stool of infected individuals, eventually ending up in the wastewater treatment plant. The presence of SARS-CoV-2 in human waste presents the opportunity to potentially monitor wastewater for SARS-CoV-2 to estimate the number of infections in the community and provide an ‘early warning system’ for future SARS-CoV-2 outbreaks. The goal of this research is to develop methods to monitor for SARS-CoV-2 in wastewater and to connect these measurements to epidemiology models. In addition, the project team will coordinate wastewater monitoring efforts for SARS-CoV-2 globally. If successful, this research could lead to other similar monitoring efforts for other viral outbreaks and protect the health of the Nation. SARS-CoV-2 (i.e., 2019-nCoV) is identified as the cause of an outbreak of respiratory illness that is now a global pandemic causing significant disruption to medical services and commerce. Significant uncertainties about the prevalence of this virus remain. This information which is vital to inform control recommendations and determine the case fatality rate. The recent detection of SARS-CoV-2 in stool raises the possibility of using wastewater-based epidemiological approaches to estimate the community prevalence of SARS-CoV-2. In this approach, molecular quantification of SARS-CoV-2 will be combined with epidemiological data to model outbreak dynamics and estimate the overall prevalence of the virus in the community over time. These data will be integrated into epidemiological models using data from public health surveillance. Data from wastewater could inform epidemiological estimates on finer spatial scales than epidemiological data and could provide indications of continued community transmission following the initial wave of the pandemic. The potential for this virus to become a seasonally transmitted endemic pathogen like influenza and other coronaviruses would make this type of analysis increasingly informative. Technical developments resulting from this research include improved sample handling methods, molecular quantification approaches, integration of the resulting data into epidemiological models, as well as coordination with domestic and international collaborators to standardize methodology. There is significant scientific interest in using wastewater to monitor for SARS-CoV-2 beyond the current outbreak. This research will inform such efforts and help respond to future outbreaks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

全球 COVID-19 大流行对人类健康和经济造成了巨大影响，给研究界带来了一系列必须实时解决的独特挑战。管理任何流行病的关键是准确估计社区内有多少人被感染。引起 COVID-19 的病毒 SARS-CoV-2 通过感染者的粪便排出，最终进入废水处理厂。人类排泄物中存在 SARS-CoV-2，这为监测废水中的 SARS-CoV-2 提供了机会，以估计社区中的感染人数，并为未来的 SARS-CoV-2 爆发提供“早期预警系统”。这项研究的目标是开发监测废水中 SARS-CoV-2 的方法，并将这些测量结果与流行病学模型联系起来。此外，项目团队将协调全球 SARS-CoV-2 废水监测工作。如果成功，这项研究可能会导致对其他病毒爆发的其他类似监测工作，并保护国家的健康。 SARS-CoV-2（即 2019-nCoV）被确定为呼吸道疾病爆发的原因，该疾病现已成为全球大流行病，对医疗服务和商业造成严重破坏。该病毒的流行情况仍然存在重大不确定性。这些信息对于提供控制建议和确定病死率至关重要。最近在粪便中检测到 SARS-CoV-2 提出了使用基于废水的流行病学方法来估计 SARS-CoV-2 社区患病率的可能性。在这种方法中，SARS-CoV-2 的分子定量将与流行病学数据相结合，以模拟疫情爆发动态并估计病毒在社区中随时间的总体流行情况。这些数据将利用公共卫生监测数据整合到流行病学模型中。与流行病学数据相比，废水数据可以为流行病学估计提供更精细的空间尺度，并可以提供第一波大流行后社区持续传播的迹象。这种病毒有可能像流感和其他冠状病毒一样成为季节性传播的地方性病原体，这将使此类分析的信息量越来越大。这项研究带来的技术发展包括改进的样本处理方法、分子定量方法、将所得数据整合到流行病学模型中，以及与国内和国际合作者协调以标准化方法。在当前疫情爆发之后，利用废水监测 SARS-CoV-2 具有重大的科学意义。这项研究将为此类努力提供信息，并帮助应对未来的疫情爆发。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。