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: 10471989
• 负责人: Jelena Srebric
• 金额: $ 21.58万
• 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/10471989
• 关键词: Accounting; Address; Aerosols; Air; Air Movements; Biological Assay; Biostatistics Core; Breathing; Caliber; Carbon Dioxide; Chest; Clinical; Cohort Studies; Controlled Environment; Core Facility; Coupled; Data; Data Set; Deposition; Development; 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; Nature; Participant; Particle Size; Positioning Attribute; Prevention; Process; Public Health; Randomized Controlled Trials; Research Project Grants; Risk; Route; Sampling; Sanitation; Scientist; Shapes; Source; Spatial Distribution; Technology; Temperature; Testing; Time; Translating; Translations; Validation; Viral; Virus; Virus Shedding; Work; aerosolized; analytical tool; base; cohort; data collection site; design; experimental study; field study; flu transmission; human subject; infection rate; influenzavirus; innovative technologies; novel; particle; sample collection; 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气溶胶传播流感的重要性