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Predictive models for determining the fate of nonculturable and difficult-to-culture viruses in disinfection processes

Predictive models for determining the fate of nonculturable and difficult-to-culture viruses in disinfection processes
用于确定消毒过程中不可培养和难以培养病毒命运的预测模型
批准号:
2015187
负责人:
Krista Wigginton
金额:
$35.0万
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
项目状态:
已结题
起止时间:
2020-08-01 至 2024-07-31

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中文摘要
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英文摘要
Viruses such as norovirus, rotavirus, and enteroviruses are major causes of waterborne illness. Conventional water treatment processes like coagulation, sedimentation, and filtration are not very effective at removing viruses. As a result, the removal and inactivation of viruses in water treatment plants rely heavily on disinfection processes. However, the effectiveness of virus disinfection cannot be tested in most water quality laboratories. This is due to the fact that many infectious viruses either cannot be grown outside of the human body or require facilities with very high levels of biosafety that are not available to most researchers. The goal of this research project is to develop new fundamental knowledge on the effectiveness of disinfection on all viruses including new pathogens such as the COVID-19 virus. To achieve this goal, the investigator proposes to carry out inactivation experiments on a group of structurally diverse waterborne-viruses using UV light, free chlorine, and chlorine dioxide as model disinfectants. The data collected from these experiments will be used to develop new models and predictive tools. Successful completion of this project will benefit society through the development of new knowledge and tools for identifying non-infectious and easy-to-grow surrogates for testing and validating virus disinfection efficiency at water treatment plants. Further benefits to society will be achieved through student education and training via the integration of the project findings into a new cross-disciplinary course on the roles that viruses play in ecology, biotechnology, and infectious diseases. Waterborne viruses are a major cause of illness worldwide. Disinfection has emerged as a critical unit operation used in water treatment to inactivate waterborne viruses and stop their transmission. However, most academic, municipal, and industrial water quality laboratories do not have adequate facilities and tools to measure the effectiveness of virus disinfection. Although non-infectious and easy-to-grow viruses are commonly employed as surrogates to evaluate disinfection efficiency, no consistent framework is available for selecting such surrogates. In addition, there is limited published data on the extent and rates of virus disinfection. The goal of this research is to address these knowledge gaps in virus disinfection. To advance this goal, the PI will carry out an integrated experimental and modeling program organized around three specific tasks. In Task 1, new virus inactivation experiments will be conducted to expand the available dataset using culture methods to grow the target viruses and UV radiation, free chlorine, and chlorine dioxide as model disinfectants. In Task 2, the data collected in Task 1 will be utilized to develop and validate structure-activity relationships (SARs) for predicting the extent and rate of virus inactivation. In Task III, the PI will leverage the new data, insight, and SARs obtained from Tasks I and II to identify more effective surrogates for testing and validating the efficacy of virus inactivation by UV radiation and chlorine-based disinfectants. Successful completion of this project has potential for transformative impact through the development of new insight and tools to predict the efficiency of virus disinfection in water treatment systems.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.
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会议论文
Collaborative Research: National Symposium on PRedicting Emergence of Virulent Entities by Novel Technologies (PREVENT)
Collaborative Research: RAPID: Coronavirus persistence, transmission, and circulation in the environment
CAREER: Wastewater Treatment as a Conduit and Control of Emerging Respiratory Viruses in the Environment
EAGER: Dose-Response Disinfection Curves for Human Norovirus with Novel Mouse Model
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
河北南部地区灰霾的来源和形成机制研究
  • 批准号:
    41105105
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    25.0万元
  • 批准年份:
    2011
  • 负责人:
    王丽涛
  • 依托单位:
保险风险模型、投资组合及相关课题研究
  • 批准号:
    10971157
  • 项目类别:
    面上项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2009
  • 负责人:
    胡亦钧
  • 依托单位:
RKTG对ERK信号通路的调控和肿瘤生成的影响