Developing and Applying Analytical Models of Influenza Transmission

流感传播分析模型的开发和应用

• 批准号: 10645170
• 负责人: Jelena Srebric
• 金额: $ 18.43万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10645170
• 关键词: Accounting; Address; Aerosols; Air; Air Movements; Biological Assay; Biostatistics Core; Breathing; Carbon Dioxide; Chest; Clinical; Cohort Studies; Collection; Controlled Environment; Core Facility; Coupled; Data; Data Set; Deposition; Development; Diameter; Disinfection; Dose; Environment; Environmental Monitoring; Equation; Exhalation; Experimental Designs; Exposure to; Face; Ferrets; Formulation; Generations; Germicide; Household; Human; Humidity; Indoor environment; Influenza; Intervention; Investigation; Knowledge; Link; Liquid substance; Location; Measurable; Measurement; Measures; Modeling; Nasopharynx; Nature; Participant; Particle Size; Positioning Attribute; Predictive Analytics; Prevention; Process; Public Health; Randomized, Controlled Trials; Research Project Grants; Risk; Risk Assessment; Route; Sampling; Sanitation; Scientist; Shapes; Source; Spatial Distribution; Technology; Temperature; Testing; Time; Translating; Translations; Validation; Viral; Virus; Virus Integration; Virus Shedding; Work; aerosolized; analytical tool; cohort; data collection site; design; experimental study; field study; flu transmission; human subject; infection rate; influenzavirus; innovative technologies; meter; novel; particle; submicron; therapy design; tool; transmission process; user-friendly; ventilation; viral transmission; web-based tool

Our current scientific knowledge indicates the importance of influenza transmission via exhaled viral bioaerosols over short and long ranges in indoor environments. The turbulent nature of indoor airflows coupled with the dynamic nature of exhaled bioaerosol sources and the poor understanding of fundamental source terms (including distribution of infective virus by aerosol size and number of viral particles per aerosol) creates difficulties in predicting and tracking aerosol-driven transmission. To address this challenge, novel sampling, collection, and infective virus assay technologies developed in the Advanced Bioaerosol Technology Core (ABTC) will allow the Clinical and Biostatistics Core (CBC) and Research Project 1 (RP1) to design and implement a cohort study capable of collecting critical data sets from both the cohort human subject exhaled breath and the controlled environment of the clinical facility where the cohort study will take place. Based on these critical datasets, Research Project 2 (RP2) will develop both well-mixed and high-fidelity analytical models for deployment in other cohort studies and physical tracking of viral bioaerosol from cohort donors to the recipients. This direct physical bioaerosol link is important to track actual exposure of recipients to viral bioaerosols based on both data and high -fidelity models. Furthermore, this link will enable translation of both cohort data and high-fidelity model results into well-mixed analytical models capable of accounting of quanta (dose) for modeling of risk of influenza transmission. A careful design of the cohort study experiment setup in the clinical facility is the first aim in this RP2 project (Aim 1). The setup design will include on-site data collection on ventilation rates and installation of environmental controls with UV air disinfection. Furthermore, Computational Fluid Dynamics (CFD) models will allow to define a face shield shape that will block sprayborne exposure with minimal impact on aerosols. The cohort study in RP1 will use both the identified face shield shape and the environmental controls for the interventions. The data from the intervention cohort studies will support the second aim in RP2 focused on analytical modeling of aerosol-driven transmission of influenza (Aim 2). In this most important aim of RP2, we will characterize the quanta (dose) that resulted in recipient cases of influenza, allowing us to link the dose to both bioaerosol shedding rate from exhaled breath measurements and environment aerosol fate. The aerosol concentration and ultimately aerosol fate will be available through validated high-fidelity modeling of temporal and spatial distributions of bioaerosols. A rigorous validation process of our high-fidelity models will use both continuously monitored environmental data (CO2, temperature, humidity) and viral bioaerosol data. These unique data sets will allow the team to create different type of influenza transmission models to distinguish between the short and long range bioaerosols. The final step is to extend our analytical models to other environments such as household cohort and ferret influenza studies. RP2 will provide both analytical models and a web-based tool for user-friendly access in the field.

我们目前的科学知识表明，通过呼出的病毒生物素化合物传播流感的重要性 在室内环境中的短期和长范围内。室内气流的动荡性以及 呼出的生物美感来源的动态性质和对基本来源术语的不良理解 （包括通过气雾剂大小和每个气溶胶的病毒颗粒数量分布） 在预测和跟踪气溶胶驱动的传输方面遇到困难。为了应对这一挑战，新颖的抽样， 收集和感染性病毒测定技术在先进的生物美洲技术核心中开发 （ABTC）将允许临床和生物统计学核心（CBC）和研究项目1（RP1）来设计和 实施一项能够从两个人类主题中收集关键数据集的队列研究 呼吸和将进行队列研究的临床设施的受控环境。基于 这些关键数据集，研究项目2（RP2）将开发混合良好和高保真分析模型 用于在其他队列研究中部署和病毒生物Aerosol的物理跟踪，从队列供体到 收件人。这种直接的物理生物美感链接对于跟踪接收者的实际暴露于病毒很重要 基于数据和高足够模型的Bioaerosols。此外，此链接将使两者都翻译 队列数据和高保真模型导致良好的分析模型能够计算量子 （剂量）用于建模流感传播风险。仔细设计队列研究实验设置 临床设施是该RP2项目的第一个目标（AIM 1）。设置设计将包括现场数据收集 使用紫外线消毒的通风速率和环境控制的安装。此外， 计算流体动力学（CFD）模型将允许定义面部盾牌形状，以阻止喷雾 暴露对气溶胶的影响最小。 RP1中的队列研究将同时使用确定的面罩 以及干预措施的环境控制。干预队列研究的数据将支持 RP2的第二个目标集中在流动驱动的流感传播的分析模型上（AIM 2）。在 RP2的最重要目的，我们将表征导致接受者的量子（剂量） 流感，允许我们将剂量与呼气的呼吸测量和 环境气溶胶命运。气溶胶浓度和最终可通过气溶胶命运可通过 经过验证的生物溶质的时间和空间分布的高保真模型。严格的验证过程 我们的高保真模型将使用不断监控的环境数据（CO2，温度，湿度） 和病毒生物溶质数据。这些独特的数据集将使团队能够创建不同类型的流感 传输模型，以区分短距离和远程生物溶质。最后一步是扩展我们 分析模型，例如家庭队列和雪貂流感研究。 RP2将提供 分析模型和基于Web的工具，用于在现场访问用户友好的访问。