CAREER: Wastewater Counts: Real-time de facto Population Estimation for Quantitative Wastewater-based Epidemiology

职业：废水计数：基于废水的定量流行病学的实时实际人口估计

• 批准号: 2047470
• 负责人: Fangqiong Ling
• 金额: $ 50万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2047470&HistoricalAwards=false
• 关键词: CAREER; Wastewater; Counts; Real; time

Wastewater-based epidemiology (WBE) has emerged as a complementary approach to existing clinical tools to track the spread of infectious disease. WBE is based on using microbial biomarkers in wastewater to monitor the onset, spread, and community transmission of infectious diseases. Although WBE has provided valuable insight into the spread of SARS-CoV-2 virus during the COVID-19 pandemic, much work remains to be done to enable accurate quantitative estimates using this technique. The goal of this CAREER project is to address this critical challenge through the development of computational approaches, models, and tools to accurately predict the size of a disease outbreak from wastewater biomarker data. Successful completion of this project will benefit society through the development of new and experimentally validated computational tools to predict community disease spread. This will allow a fuller exploitation of the large amount of WBE data that are being collected in the United States to advance public health. Further benefits to society will be achieved through the mentoring of a doctoral student at Washington University in St. Louis. Additional benefits derive from the development of an education kit focused on environmental data sciences to advance science literacy in K-12 students.The overarching goal of this CAREER project is to advance the science and engineering of wastewater-based epidemiology (WBE) through the development and validation of new computational tools to estimate the size of affected population in real time from biomarkers in untreated wastewater. This will be achieved through specific research designed to (1) build a computational framework for wastewater microbiome-based population models, (2) develop and experimentally validate models and computational tools for estimating the size affected populations in infectious disease outbreaks using community wastewater surveillance data, and (3) apply these new models and tools to evaluate and improve the design of WBE sampling programs. The educational plan will (1) engage wastewater treatment and public health practitioners in refining and disseminating microbiome-based population models and design tools for WBE, 2) enhance the interdisciplinary training of environmental engineering undergraduate and graduate students by integrating data science into the educational curriculum, and 3) develop and distribute a K-12 educational kit on environmental data science based on Next Generation Science Standards. The successful completion of this project has strong potential to transform our ability to track disease outbreaks through the development of new computational tools for WBE surveillance programs. The broader impacts of this project will be enhanced by training practitioners and providing educational resources to diverse student populations at the K-12, college, and postgraduate levels.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.

基于废水的流行病学（WBE）已成为追踪传染病传播的现有临床工具的一种补充方法。 WBE基于废水中使用微生物生物标志物来监测传染病的发作，传播和社区传播。尽管WBE在COVID-19大流行期间对SARS-COV-2病毒的传播提供了宝贵的见解，但使用此技术可以实现准确的定量估计还有许多工作要做。该职业项目的目的是通过开发计算方法，模型和工具来应对这一关键挑战，以准确预测废水生物标志物数据中疾病爆发的大小。成功完成该项目将通过开发新的和实验验证的计算工具来预测社区疾病扩散，从而使社会受益。这将允许对美国收集的大量WBE数据进行更全面的利用，以提高公共卫生。通过在圣路易斯华盛顿大学指导一名博士生的指导，将获得进一步的好处。额外的好处源于开发侧重于环境数据科学，以推进K-12学生的科学素养。该职业项目的总体目标是通过开发和验证新的计算工具的开发和验证，以估算来自生物市场中受影响的人群的大小，从而促进了基于废水的流行病学（WBE）的科学和工程。 This will be achieved through specific research designed to (1) build a computational framework for wastewater microbiome-based population models, (2) develop and experimentally validate models and computational tools for estimating the size affected populations in infectious disease outbreaks using community wastewater surveillance data, and (3) apply these new models and tools to evaluate and improve the design of WBE sampling programs.教育计划将（1）与废水治疗和公共卫生从业人员一起介入和传播基于微生物组的人群模型和设计工具，2）通过将数据科学整合到教育课程中，并在k-12教育方面发展和分配了基于环境学的科学，从而增强了对环境工程本科生和研究生的跨学科培训。该项目的成功完成具有强大的潜力，可以通过开发用于WBE监视计划的新计算工具来改变疾病暴发的能力。培训从业人员将增强该项目的更广泛影响，并为K-12，大学和研究生级别的不同学生提供教育资源。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来获得支持的。

项目成果

Emerging investigator series: meta-analyses on SARS-CoV-2 viral RNA levels in wastewater and their correlations to epidemiological indicators

• DOI: 10.1039/d2ew00084a
• 发表时间: 2022-05-04
• 期刊: ENVIRONMENTAL SCIENCE-WATER RESEARCH & TECHNOLOGY
• 影响因子: 5
• 作者: Mantilla-Calderon, David;Huang, Kaiyu (Kevin);Ling, Fangqiong
• 通讯作者: Ling, Fangqiong