RAPID COVID-19 DCL response: Wastewater Pathogen Tracking Dashboard

RAPID COVID-19 DCL 响应：废水病原体跟踪仪表板

• 批准号: 2033137
• 负责人: Rachel Spurbeck
• 金额: $ 19.74万
• 依托单位: Battelle Memorial Institute
• 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: 2020-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2033137&HistoricalAwards=false
• 关键词: RAPID; COVID; 19; DCL; response

Monitoring the spread of COVID-19 within communities is essential to enable outbreak control measures such as social distancing or contact tracing to be effective. The goal of this project is to build a system to detect and quantify COVID-19 from city wastewater to identify neighborhoods that are at highest risk as the virus spreads. Low or undetectable COVID-19 counts are expected to be observed in wastewater from neighborhoods where the outbreak is under control, whereas they will be higher in regions where social distancing or contact tracing is needed to stop viral spread. This tracking system is adaptable to other pathogens that cause outbreaks of public health concern as well, and it will help ensure public safety as the economy is re-opening and afterwards by detecting second-wave outbreaks of which the public should be aware. This tracking system will provide real time insight into community spread and prevalence of COVID-19 by building risk models from wastewater data and comparing those to models built from other public health data. A broader impact from this research will be the development of a publicly accessible, web-based Wastewater Pathogen Tracking Dashboard (WPTD). Several studies have demonstrated that the virus that causes COVID-19, SARS-CoV-2, is detectable in human waste and in the influent of wastewater treatment plants using diagnostic techniques such as qPCR. Compared to traditional public health risk estimation models, sampling of wastewater offers a more immediate and passive approach to population surveillance that can be tied to source tracing and socioeconomic impacts without depending on an already overburdened healthcare system. This work will go beyond the state of the art to include virome sequencing to determine prevalence of SARS-CoV-2 and other viral pathogens and long read sequencing from four locations to quantify and detect viral mutations, that may correlate with differential disease severity. The project will produce a predictive risk model to identify neighborhoods where contact tracing should be implemented due to high abundance of SARS-CoV-2 in the wastewater relative to the number of confirmed cases. This model will be developed and compared to models built from public health data to enable prediction of neighborhoods that have cleared the virus or are having new outbreaks. Virome analysis will enable extension to other pathogens of public concern and development of a dashboard for data presentation to public officials to enable informed policy decisions regarding pandemic response.This RAPID award is made by the Ecology and Evolution of Infectious Diseases Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) ActThis 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.

监视Covid-19在社区内的传播对于实现爆发控制措施（例如社交距离或接触跟踪）的蔓延至关重要。该项目的目的是建立一个从城市废水中检测和量化共vid-19的系统，以确定随着病毒传播而处于最高风险的社区。预计在疫情受到控制的社区的废水中，预计将观察到低或不可发现的Covid-19计数，而在需要社交距离或接触式追踪以停止病毒蔓延的地区中，它们将更高。这种跟踪系统也适用于引起公共卫生问题爆发的其他病原体，它将有助于确保公共安全，因为经济正在重新开放，然后通过检测公众应意识到的第二波爆发。该跟踪系统将通过从废水数据中构建风险模型，并将这些模型与从其他公共卫生数据构建的模型进行比较，从而为Covid-19提供实时洞察力。这项研究的更广泛影响将是开发公共可访问的基于网络的废水病原体跟踪仪表板（WPTD）。几项研究表明，在人类废物和使用QPCR等诊断技术中，可以在人类废物和废水处理厂的影响中检测到COVID-19，SARS-COV-2的病毒。与传统的公共卫生风险估计模型相比，废水的采样提供了一种更直接和被动的人口监视方法，可以将其与所产生的追踪和社会经济影响相关，而不依赖于已经过度负担的医疗保健系统。这项工作将超越最新技术，以包括病毒蛋白测序，以确定SARS-COV-2和其他病毒病原体的患病率以及从四个位置进行长期读取测序以量化和检测病毒突变，这可能与鉴别疾病严重程度相关。该项目将产生一个预测风险模型，以确定应由于确认案件的数量而在废水中的SARS-COV-2高丰度，因此应实施接触示意图。该模型将被开发并与从公共卫生数据构建的模型进行比较，以预测清除病毒或正在发生新爆发的社区。 Virome analysis will enable extension to other pathogens of public concern and development of a dashboard for data presentation to public officials to enable informed policy decisions regarding pandemic response.This RAPID award is made by the Ecology and Evolution of Infectious Diseases Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) ActThis award reflects NSF's statutory mission and has been deemed值得通过基金会的智力优点和更广泛的影响审查标准来通过评估来支持。