Development and Proof-of-Concept Implementation of the South Florida Miami RADx-rad SARS-CoV-2 Wastewater-Based Surveillance Infrastructure

南佛罗里达州迈阿密 RADx-rad SARS-CoV-2 废水监测基础设施的开发和概念验证实施

• 批准号: 10321001
• 负责人: Christopher Edward Mason
• 金额: $ 234.12万
• 依托单位: UNIVERSITY OF MIAMI CORAL GABLES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10321001
• 关键词: 2019-nCoV; Address; Area; Attention; Behavioral; Big Data to Knowledge; Bioinformatics; Biometry; COVID-19; COVID-19 detection; COVID-19 monitoring; COVID-19 outbreak; COVID-19 patient; COVID-19 treatment; Cities; Collaborations; Communicable Diseases; Communities; Community Hospitals; Core Facility; Coronavirus; Data; Data Collection; Data Coordinating Center; Data Set; Detection; Development; Diagnostic tests; Disease Surveillance; Early Diagnosis; Ensure; Epidemiology; Ethical Issues; Ethics; Evaluation; FAIR principles; Faculty; Filtration; Florida; Genomics; Geography; Health; Hospitals; Hour; Human; Infrastructure; International; Link; Maps; Measurement; Medicine; Metadata; Metagenomics; Methodology; Methods; Modeling; Molecular; Monitor; New York; New York City; Patients; Population; Prevalence; Process; Protocols documentation; Quantitative Reverse Transcriptase PCR; RADx Radical; RNA; Rapid diagnostics; Recovery; Reproducibility; Research; Resource Sharing; Resources; Sampling; Services; Sewage; Specificity; Specimen; Standardization; Students; Surveillance Program; System; Technical Expertise; Techniques; Technology; Testing; Therapeutic; U-Series Cooperative Agreements; Ultrafiltration; United States National Institutes of Health; Universities; Viral; Virus; Work; base; biobank; community based research; community transmission; computerized data processing; data management; data quality; data standards; detection method; emerging pathogen; experience; improved; informatics infrastructure; informatics tool; metatranscriptomics; nasal swab; operation; outreach; predictive modeling; programs; sample collection; surveillance data; surveillance network; transcriptome sequencing; viral detection; wastewater monitoring; wastewater samples; wastewater sampling; wastewater surveillance; working group

PROJECT SUMMARY The University of Miami (UM), with three primary campuses in Miami, Florida, is geographically spread within one of the worst current COVID-19 hotbeds. UM has deployed an elaborate human surveillance testing, tracking and tracing (3T) system to monitor the student body, faculty, and staff. This 3T system includes a major hospital that is part of UM and that treats COVID-19 patients. To augment this COVID-19 monitoring system, UM has deployed a pilot wastewater surveillance program for detecting SARS-CoV-2 from clusters of buildings on campus. Weill Cornell Medicine (WCM) is located in New York City, NY, an area that until recently had one of the worst outbreaks of COVID-19. WCM has established an international consortium for SARS-CoV-2 environmental surveillance, including in NYC and globally with the MetaSUB Consortium, which is creating metagenomic and metatranscriptomic maps of the world’s sewage. Based on this work at both UM and WCM, this proposal aims to develop, implement, and demonstrate effective and predictive wastewater surveillance by optimizing sampling, concentration, and detection strategies. Working closely with the RADx-rad Data Coordination Center (DCC), this application (SF-RAD) will develop and implement data standards and informatics infrastructure and perform integrative analyses to make all data, results, and models available to the community, thus providing a critical contribution to the national SARS-COV-2 RADx-rad Wastewater Detection Consortium. Our objectives will be addressed through three aims. Aim 1: Data Standardization, focuses on developing and implementing data standards and quality metrics, and establishing the operational infrastructure to manage SARS-CoV-2 wastewater-based surveillance datasets and metadata. Aim 2: Wastewater Characterization, focuses on optimizing wastewater surveillance protocols and parameters for wastewater sampling, sample concentration, and viral detection technologies. Aim 3: Integration with Human Health Surveillance, focuses on metatranscriptomic analyses and on the integration of wastewater quantification data with community and hospital COVID-19 prevalence, to develop predictive models to detect local and community level spread of COVID-19. All data will be made Findable, Accessible, Interoperable and Reusable (FAIR) in close collaboration with the DCC, and will be collected and managed with attention to ethical issues in surveillance and data management, including efforts to ensure research rigor and reproducibility. The results from this proposal will develop and deploy experimental and informatics infrastructure and operations as part of the national RADx-rad SARS-CoV-2 wastewater surveillance network and will provide a proof-of-concept implementation to use wastewater for infectious disease surveillance for early detection of localized COVID-19 outbreaks.

项目摘要 迈阿密大学（UM）在佛罗里达州迈阿密的三个主要校园在地理上传播 当前最糟糕的Covid-19温床之一。 UM部署了精心设计的人类监视测试，跟踪 以及跟踪（3T）系统，以监视学生团体，教职员工。这个3T系统包括一家大型医院 那是UM的一部分，可以治疗199例患者。为了增加此COVID-19监测系统，UM具有 部署了一个试点废水监视计划，用于从建筑物集群中检测SARS-COV-2 校园。 Weill Cornell Medicine（WCM）位于纽约州纽约市，直到最近才有一个 Covid-19的最严重爆发。 WCM已建立了一个用于SARS-COV-2的国际财团 环境监视，包括纽约市和全球范围内的元穆斯布联盟，这正在创建 世界污水的宏基因组和元文字图。基于UM和WCM的这项工作， 该建议旨在通过 优化采样，浓度和检测策略。与RADX-RAD数据紧密合作 协调中心（DCC），此应用程序（SF-RAD）将制定和实施数据标准和 信息基础架构并执行集成分析，以使所有数据，结果和模型可用于 社区，从 财团。我们的目标将通过三个目标解决。目标1：数据标准化，专注于 制定和实施数据标准和质量指标，并建立运营基础架构 管理基于SARS-COV-2废水的监视数据集和元数据。目标2：废水 表征，重点是优化废水监视方案和废水参数 目标3：与人类健康融为一体 监视，侧重于元文字分析和废水量化数据的整合 随着社区和医院Covid-19的患病率，开发预测模型来检测本地和社区 COVID-19的水平传播。所有数据都将在 与DCC密切合作，并将收集和管理 监视和数据管理，包括确保研究严格和可重复性的努力。结果 根据该提案将开发和部署实验性和信息信息基础设施和运营 国家RADX-RAD SARS-COV-2废水监视网络，将提供概念验证 实施使用废水进行传染病监测，以尽早发现局部covid-19 爆发。