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

基本信息

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

项目摘要

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.

监测社区内 COVID-19 的传播对于保持社交距离或接触者追踪等疫情控制措施发挥作用至关重要。该项目的目标是建立一个系统来检测和量化城市废水中的 COVID-19，以识别病毒传播时风险最高的社区。预计在疫情得到控制的社区的废水中会观察到较低或无法检测到的 COVID-19 计数，而在需要保持社交距离或接触者追踪以阻止病毒传播的地区，该计数会更高。该跟踪系统也适用于引起公共卫生问题爆发的其他病原体，并且将有助于在经济重新开放时以及之后通过检测公众应注意的第二波疫情来确保公共安全。该跟踪系统将根据废水数据构建风险模型并将其与根据其他公共卫生数据构建的模型进行比较，从而实时洞察 COVID-19 的社区传播和流行情况。这项研究的更广泛影响将是开发一个可公开访问的、基于网络的废水病原体跟踪仪表板（WPTD）。多项研究表明，使用 qPCR 等诊断技术可以在人类废物和废水处理厂进水中检测到导致 COVID-19（SARS-CoV-2）的病毒。与传统的公共卫生风险评估模型相比，废水采样为人口监测提供了一种更直接、更被动的方法，可以与源头追踪和社会经济影响联系起来，而无需依赖已经不堪重负的医疗保健系统。这项工作将超越现有技术，包括病毒组测序以确定 SARS-CoV-2 和其他病毒病原体的流行情况，以及从四个位置进行长读测序以量化和检测病毒突变，这可能与不同的疾病严重程度相关。该项目将建立一个预测风险模型，以确定由于废水中 SARS-CoV-2 含量相对于确诊病例数较高而应实施接触者追踪的社区。该模型将被开发并与根据公共卫生数据构建的模型进行比较，以预测已经清除病毒或正在爆发新疫情的社区。病毒组分析将能够扩展到公众关注的其他病原体，并开发一个向公职人员提供数据的仪表板，以便就大流行应对做出明智的政策决策。该快速奖由环境部传染病生态学和进化项目颁发生物学，使用冠状病毒援助、救济和经济安全 (CARES) 法案的资金。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。