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: 2147070
• 负责人: Mark Weir
• 金额: $ 2.99万
• 依托单位: Ohio State University
• 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=2147070&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病原体，如果遗传，可能会在包括军团疾病和庞蒂亚克热的人类中引起严重的疾病。尽管对居民，商业和机构建筑以及医疗机构中的军团菌的航音和吸入的知识越来越大，但疾病爆发仍在增加。自1976年第一次军团菌爆发以来，已经进行了许多基准，飞行员和现场规模的研究，以制定缓解和预防疾病暴发的策略和准则。但是，建立一个定量框架以预测建筑物中的军团菌疾病爆发仍然难以捉摸。这个多机构合作项目的总体目标是促进对建筑水系统中军团菌增长的基本了解，并利用这一新知识来开发和验证计算模型，以预测军团菌增长和建筑物暴露的潜在热点。该项目的成功完成将通过开发新的基本知识和建模工具来使社会受益，从而确定建筑物前提管制系统的设计/操作参数和环境条件，这些系统最大程度地影响军团菌的增长和持久性。将通过学生的教育和培训获得进一步的社会利益，包括对两名研究生的心理和亚利桑那州立大学，纽约州卫生系和新泽西学院的一名本科生的心理。肺炎军团菌（L. pneumophila）是一种感染性的病原体，由于其引起军团疾病（LD），严重的肺炎的能力以及控制细菌在饮用水系统中的持久性的困难。 L.肺炎在大型前提管道系统中繁荣发展，例如在医院中发现的。常用的消毒剂无效地从前提管道系统中根除肺炎乳杆菌。此外，没有经过验证的模型可以预测建筑物水系统中可行的军团菌细胞的浓度。该项目的总体目标是开发和验证一个计算模型，该模型可以预测建筑物前提下的肺炎乳杆菌在建筑物的前提中的生长和持久性，这是系统设计，操作参数和环境条件的函数。该研究的特定对象是：（1）使用最先进的快速抽样技术来量化军团菌的浓度，水质参数，操作参数，以及在纽约州卫生部已有的纽约州卫生部已持续合作的数据丰富的建筑物和/或疾病案例中的数据丰富的建筑物中建造设计规范； （2）使用针对性和多因素实验的多元参数空间中的Legionella动力学信息，其中包括参数的组合，包括生物膜条件，消毒剂残留浓度，温度和养分负荷； （3）开发和验证一个计算模型（具有特定地点信息和更新的动力学信息），以预测前提管道系统中的军团菌持久性和增长，这将为建筑物中LD爆发的定量微生物风险评估（QMRA）提供信息。通过开发新的基本知识和建模工具，可以成功完成该项目的成功完成，以支持对建筑物中与LD爆发相关的人类健康风险的更准确估计。为了消除该项目的发现，首席研究人员（PIS）计划进行外展活动（包括针对性的研讨会和会议），以呈现其研究结果的结果以及来自广泛的利益相关者的良好反馈，包括美国供暖，冷藏，冷藏和空调工程师（Ashrae Workeristion（Aseming Working Atimise）（AWWA），以及USIBIBS Working Atimans（AWWA），以及USAWA WASICAS（AWWA），以及USIBIBER WORKISION（AWWA）集团。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估被认为是宝贵的支持。