Collaborative Research: An integrative framework for decision support models including plumbing system dynamics and value of information to meet Legionella control goals

协作研究：决策支持模型的综合框架，包括管道系统动力学和信息价值，以满足军团菌控制目标

• 批准号: 2147029
• 负责人: Alexis Mraz
• 金额: $ 6.48万
• 依托单位: The College of New Jersey
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2147029&HistoricalAwards=false
• 关键词: Collaborative; Research; integrative; framework; decision

Legionella is a waterborne pathogen, that if inhaled, can cause severe illness in humans including Legionnaires’ disease and Pontiac fever. Despite growing knowledge about Legionella aerosolization and inhalation in residential, commercial, and institutional buildings and in healthcare facilities, disease outbreaks are increasing. Since the first Legionella outbreak in 1976, numerous bench, pilot, and field-scale studies have been conducted to develop strategies and guidelines for the mitigation and prevention of disease outbreaks. However, the development of a quantitative framework to predict Legionella disease outbreak in buildings has remained elusive. The overarching goal of this multi-institution collaborative project is to advance the fundamental understanding of Legionella growth in building water systems and leverage this new knowledge to develop and validate a computational model to predict potential hotspots of Legionella growth and exposure in buildings. The successful completion of this project will benefit society through the development of new fundamental knowledge and modeling tools to identify the design/operational parameters and environmental conditions of a building’s premise plumbing system that most affect the growth and persistence of Legionella. Further benefits to society will be achieved through student education and training including the mentoring of two graduate students and an undergraduate student at Arizona State University, the New York State Department of Health, and the College of New Jersey. Legionella pneumophila (L. pneumophila) is an infectious pathogen of increasing concern due to its ability to cause Legionnaires’ Disease (LD), a severe pneumonia, and the difficulty in controlling the bacteria’s persistence in drinking water systems. L. pneumophila thrives within large premise plumbing systems such as those found in hospitals. Commonly used disinfectants are not effective in eradicating L. pneumophila from premise plumbing systems. In addition, there is no validated model to predict the concentration of viable Legionella cells in a building water system. The overarching goal of this project is to develop and validate a computational model that could predict the growth and persistence of L. pneumophila within a building’s premise plumbing as a function of system design, operational parameters, and environmental conditions. The specific objectives of the research are to: (1) Use state-of-the-art, rapid sampling techniques to quantify Legionella concentrations, water quality parameters, operational parameters, and building design specifications in data-rich buildings with known Legionella problems and/or disease cases where the New York State Department of Health has ongoing partnerships; (2) Derive Legionella kinetic information over a multivariate parameter space using targeted and multifactorial experiments with a combination of parameters including biofilm conditions, disinfectant residual concentrations, temperatures, and nutrient loadings; and (3) Develop and validate a computational model (with site-specific information and updated kinetic information) to predict Legionella persistence and growth in premise plumbing systems that will inform quantitative microbial risk assessment (QMRA) models of LD outbreaks in buildings. The successful completion of this project has the potential for transformative impact through the development of new fundamental knowledge and modeling tools to support more accurate estimates of human health risks associated with LD outbreaks in buildings. To disseminate the findings of this project, the Principal Investigators (PIs) plan to conduct outreach events (including targeted workshops and conferences) to present the results of their research findings and solicit feedback from a broad audience of stakeholders including the Association of American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), the American Water Works Association (AWWA), and the US Environmental Protection Agency (EPA) premise plumbing working group.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.

军团菌是一种水传播的病原体，如果被吸入，会导致人类患上严重的疾病，包括军团病和庞蒂亚克热。尽管人们对住宅、商业和机构建筑以及医疗设施中的军团菌气雾化和吸入的了解越来越多，但疾病暴发仍在增加。自1976年第一次军团菌暴发以来，已经进行了大量的试验台、试点和现场规模的研究，以制定减轻和预防疾病暴发的战略和指导方针。然而，预测建筑物中军团菌病暴发的定量框架的开发仍然难以捉摸。这个多机构合作项目的首要目标是促进对建筑给水系统中军团菌生长的基本了解，并利用这一新知识开发和验证计算模型，以预测建筑物中军团菌生长和暴露的潜在热点。该项目的成功完成将通过开发新的基础知识和建模工具来识别对军团菌生长和持久性影响最大的建筑物内管道系统的设计/运行参数和环境条件，从而造福社会。将通过学生教育和培训进一步造福社会，包括指导亚利桑那州立大学、纽约州卫生部和新泽西学院的两名研究生和一名本科生。嗜肺军团菌是一种越来越受到关注的传染病病原体，因为它能引起军团病，一种严重的肺炎，并且很难控制这种细菌在饮用水系统中的持久性。嗜肺性乳杆菌在大型住宅管道系统中繁衍生息，例如医院中的管道系统。常用的消毒剂不能有效地从室内管道系统中根除嗜肺乳杆菌。此外，还没有经过验证的模型来预测建筑水系统中军团菌活细胞的浓度。该项目的主要目标是开发和验证一个计算模型，该模型可以根据系统设计、运行参数和环境条件来预测建筑物内管道内嗜肺乳杆菌的生长和持续时间。这项研究的具体目标是：(1)使用最先进的快速采样技术来量化军团菌浓度、水质参数、运行参数和建筑设计规范，这些建筑物具有已知的军团菌问题和/或纽约州卫生部持续合作的疾病病例；(2)使用目标和多因素实验，结合生物膜条件、消毒剂残留浓度、温度和营养物质负荷等参数组合，在多变量参数空间内获得军团菌动力学信息；以及(3)开发和验证一个计算模型(具有特定地点的信息和更新的动力学信息)来预测建筑物内管道系统中军团菌的持续和生长，该模型将为建筑物内LD暴发的定量微生物风险评估(QMRA)模型提供信息。这一项目的成功完成有可能通过开发新的基本知识和建模工具产生变革性影响，以支持更准确地估计与建筑物内LD暴发有关的人类健康风险。为了传播这个项目的结果，首席调查员(PI)计划开展外展活动(包括有针对性的研讨会和会议)，展示他们的研究结果，并征求广泛的利益相关者的反馈，包括美国供暖、制冷和空调工程师协会(ASHRAE)、美国水务工程协会(AWWA)和美国环境保护局(EPA)住宅管道工作组。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。