Bioinformatics Framework for Wastewater-based Surveillance of Infectious Diseases

基于废水的传染病监测的生物信息学框架

• 批准号: 10246003
• 负责人: ROLF U HALDEN
• 金额: $ 57.16万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-21 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10246003
• 关键词: 2019-nCoV; Area; Award; Bioinformatics; COVID-19; COVID-19 detection; COVID-19 monitoring; COVID-19 pandemic; Case Study; Cities; Clinical; Collaborations; Communicable Diseases; Communication; Communities; Complement; Computer Simulation; Data; Data Analyses; Data Coordinating Center; Databases; Disease; Disease Outbreaks; Disease Surveillance; Environmental Health; Epidemiologist; Epidemiology; Evaluation; Event; Foundations; Frequencies; Future; Genbank; General Population; Genetic Polymorphism; Genome; Genomics; Geographic Distribution; Geographic Locations; Goals; Harvest; Health protection; Health system; Healthcare; High-Throughput Nucleotide Sequencing; Individual; Infection; Knowledge; Measures; Methods; Mining; Molecular Virology; Monitor; Morbidity - disease rate; Movement; Neighborhoods; Parents; Peer Review; Plants; Polymerase Chain Reaction; Population; Population Surveillance; Prevention; Process; Public Health; Publishing; RADx Radical; Recording of previous events; Reporting; Research; Resolution; Resource Sharing; Resources; Reverse Transcription; SARS-CoV-2 infection; SARS-CoV-2 variant; Saliva; Sampling; Sentinel; Sequence Analysis; Serum; Sewage; Signal Transduction; Single Nucleotide Polymorphism; Surveillance Methods; Swab; System; Testing; Time; Translating; United States; United States National Institutes of Health; Viral; Viral Genome; Virus; Virus Diseases; Visualization; Work; biomedical informatics; burden of illness; cost; dashboard; data streams; infection burden; infection rate; mass casualty; mortality; novel coronavirus; pandemic disease; population health; public health intervention; response; screening; tool; transcriptome sequencing; trend; wastewater epidemiology; wastewater surveillance; web portal

Project Summary COVID-19 is expected to become one of the largest mass casualty events in the history of the United States (U.S.). Assessment of the true burden of disease in the population is needed for the prevention and mitigation of this and future viral disease outbreaks. Currently, testing of new cases (via swabs / saliva) and those previously exposed (via serum) has limited reach in the population. However, an alternative approach relying on the analysis of community wastewater can screen up to 70% of the U.S. population on a weekly basis at <0.01% of the cost of clinical screening of individuals. As a population-wide infectious disease surveillance tool, wastewater-based epidemiology (WBE) can be used to complement current surveillance methods to better understand disease burden and how these burdens differ across communities. The goal of our proposed RADx-rad supplement is to implement and evaluate a near real-time WBE framework for SARS-CoV-2 by (i) assessing in near real-time community spread of the new coronavirus, (ii) significantly increasing the fraction of the U.S. population screened, the frequency at which this testing is being completed (weekly) and the geospatial resolution of screening (from city-wide to neighborhood-specific), (iii) comparing novel coronavirus levels in wastewater with the burdens of infection, disease and mortality reported by local health systems, (iv) harvesting high throughput sequence (HTS) data on SARS-CoV-2 variants across the U.S., (v) optimizing pipelines for HTS analysis, and (vi) immediately sharing any new knowledge gained with the RADx-rad Data Coordinating Center (DCC), research community, and the general public via an expansion of our online dashboard that was pioneered by the proposing team in collaboration with the City of Tempe, AZ. We will leverage previously developed, peer-reviewed strategies for population-wide virus monitoring via reverse transcription real-time polymerase chain reaction (RT-qPCR), HTS, sequence analysis, and data communication originally developed for our parent award to quickly provide a data stream and scientific resource for managing the COVID-19 epidemic in the U.S. In Aim 1, develop a wastewater-based epidemiology (WBE) bioinformatics framework for SARS-CoV-2 at the national, city and intra-sewershed or neighborhood-level to produce RT-qPCR and SARS-CoV-2 RNA-seq data for studying the distribution of viral levels and genetic polymorphisms in the community. In Aim 2, we will evaluate a WBE bioinformatics framework for translating SARS-CoV-2 data from RT-qPCR and high- throughput sequencing into information for monitoring population health. Successful completion of this biomedical informatics project will provide the U.S. with an early warning system for SARS-CoV-2 detection and a tracking aid for public health epidemiologists seeking to reduce morbidity and mortality from infectious diseases like COVID-19 in the U.S.

项目摘要 预计Covid-19将成为曼联历史上最大的大规模伤亡事件之一 国家（美国）。预防和 缓解这种病毒疾病爆发。目前，测试新病例（通过拭子 /唾液）和 先前暴露（通过血清）的人群的影响力有限。但是，另一种方法 依靠对社区废水的分析可以在每周一次的美国人口中占70％ 基础<0.01％的个体临床筛查成本。作为人群全体传染病 监视工具，基于废水的流行病学（WBE）可用于补充当前监视 更好地了解疾病负担以及这些负担如何在整个社区中有何不同的方法。 我们提出的RADX-RAD补充剂的目标是实施和评估近乎实时的WBE SARS-COV-2框架由（i）评估新的冠状病毒的近乎实时社区传播，（ii） 显着增加了筛查的美国人口的比例，该测试的频率 完成（每周）和筛查的地理空间解决方案（从全市到邻里特定），（iii） 比较废水中的新型冠状病毒水平与感染，疾病和死亡率的负担 通过本地卫生系统，（iv）收集有关SARS-COV-2变体的高通量序列（HTS）数据 美国，（v）优化HTS分析的管道，（VI）立即共享任何新知识 通过RADX-RAD数据协调中心（DCC），研究社区和公众通过 扩展我们的在线仪表板，该仪表板是由建议团队与市政府合作的 坦佩，亚利桑那州。 我们将利用先前开发的，通过同行评审的策略，用于通过 逆转录实时聚合酶链反应（RT-QPCR），HTS，序列分析和数据 最初为我们的父母奖开发的沟通，以快速提供数据流和科学 在美国管理COVID-19的流行资源 在AIM 1中，为SARS-COV-2 AT开发基于废水的流行病学（WBE）生物信息学框架 国家，城市和隔壁或邻里级别生产RT-QPCR和SARS-COV-2 RNA-SEQ 研究社区病毒水平和遗传多态性的分布的数据。在AIM 2中，我们将 评估WBE生物信息学框架，用于翻译RT-QPCR和高级的SARS-COV-2数据 吞吐量测序到信息以监测人口健康的信息。 该生物医学信息学项目的成功完成将为美国提供预警 SARS-COV-2检测系统和寻求减少的公共卫生流行病学家的跟踪辅助 美国诸如COVID-19的传染病的发病率和死亡率在美国