Developing and Applying Analytical Models of Influenza Transmission

Information

  • Research Project
  • 10260850
  • ApplicationId
    10260850
  • Core Project Number
    U19AI162130
  • Full Project Number
    1U19AI162130-01
  • Serial Number
    162130
  • FOA Number
    RFA-AI-20-008
  • Sub Project Id
    9476
  • Project Start Date
    9/1/2021 - 2 years ago
  • Project End Date
    5/31/2026 - 2 years from now
  • Program Officer Name
  • Budget Start Date
    7/1/2021 - 2 years ago
  • Budget End Date
    6/30/2022 - a year ago
  • Fiscal Year
    2021
  • Support Year
    01
  • Suffix
  • Award Notice Date
    8/19/2021 - 2 years ago

Developing and Applying Analytical Models of Influenza Transmission

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.

IC Name
NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES
  • Activity
    U19
  • Administering IC
    AI
  • Application Type
    1
  • Direct Cost Amount
    200101
  • Indirect Cost Amount
    108396
  • Total Cost
  • Sub Project Total Cost
    308497
  • ARRA Funded
    False
  • CFDA Code
  • Ed Inst. Type
  • Funding ICs
    NIAID:308497\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZAI1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    UNIV OF MARYLAND, COLLEGE PARK
  • Organization Department
  • Organization DUNS
    790934285
  • Organization City
    COLLEGE PARK
  • Organization State
    MD
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    207425141
  • Organization District
    UNITED STATES