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

军团菌是一种水传播病原体，如果吸入，可导致人类严重疾病，包括军团病和庞蒂亚克热。尽管对军团菌在住宅、商业和机构建筑以及卫生保健设施中的雾化和吸入的了解越来越多，但疾病暴发仍在增加。自1976年第一次军团菌爆发以来，进行了大量的实验、试点和实地规模的研究，以制定减轻和预防疾病爆发的战略和准则。然而，预测建筑物中军团菌病爆发的定量框架的发展仍然难以捉摸。这个多机构合作项目的总体目标是推进对建筑供水系统中军团菌生长的基本理解，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确定最影响军团菌生长和持续的建筑物前提管道系统的设计/操作参数和环境条件，从而造福社会。通过学生教育和培训，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，将进一步造福社会。嗜肺军团菌（L. pneumophila）是一种日益引起关注的感染性病原体，因为它能够引起军团病（LD），一种严重的肺炎，并且难以控制细菌在饮用水系统中的持久性。嗜肺乳杆菌在大型设施的管道系统中繁殖，例如在医院中发现的管道系统。常用的消毒剂不能有效地根除住宅管道系统中的嗜肺乳杆菌。此外，目前还没有有效的模型来预测建筑水系统中活菌的浓度。该项目的总体目标是开发和验证一个计算模型，该模型可以预测嗜肺乳杆菌在建筑物前提管道中的生长和持久性，作为系统设计、操作参数和环境条件的函数。该研究的具体目标是：(1)使用最先进的快速采样技术，在数据丰富的建筑物中量化军团菌浓度、水质参数、操作参数和建筑设计规范，这些建筑物已知有军团菌问题和/或疾病病例，纽约州卫生部与这些建筑物有持续的合作关系；(2)结合生物膜条件、消毒剂残留浓度、温度和营养负荷等参数，通过有针对性的多因子实验，获得军团菌在多元参数空间上的动力学信息；(3)开发并验证一个计算模型（包含特定地点的信息和最新的动力学信息），以预测军团菌在住宅管道系统中的持续存在和生长，这将为建筑物中LD爆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产生变革性的影响，因为它开发了新的基础知识和建模工具，以支持更准确地估计与建筑物中致病菌爆发有关的人类健康风险。为了传播该项目的研究成果，首席研究员（pi）计划举办外展活动（包括有针对性的研讨会和会议），展示他们的研究成果，并征求广大利益相关者的反馈，包括美国采暖、制冷和空调工程师协会（ASHRAE）、美国水务协会（AWWA）、和美国环境保护署（EPA）的前提管道工作组。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.