Quantifying Environmental Variables Affecting Airborne Influenza Transmission

Icahn School Of Medicine At Mount Sinai, New York NY

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Abstract

DESCRIPTION (provided by applicant): Quantifying Environmental Variables Affecting Airborne Influenza Transmission In most temperate climates, influenza prevails in cold, dry winter months. However, in some temperate and tropical regions, influenza epidemicity is correlated with extremes of precipitation, not dryness, and can circulate at low levels essentially year-round or appear in uni- or bi-modal annual outbreaks. How environmental variables affect influenza circulation in the human population remains poorly understood, in part because the science behind airborne respiratory virus transmission crosses disciplinary boundaries between the biomedical and physical sciences, encompassing fields as diverse as virology, physiology, epidemiology, fluid mechanics, aerosol science, and climatology. Here we seek to understand how individual environmental variables - such as temperature, humidity, and airflow - cumulatively affect the transmission probability of influenza viruses in a representative mammalian experimental system. The theoretical framework behind these studies is a novel quantitative model, based upon data gathered in experimental guinea pigs, which attempts to characterize the impact of the environment on influenza virus transmission between infected and susceptible hosts. This project bridges the gap between virology and engineering in bringing together three co- investigators with relevant and complementary skill sets: Dr. Nicole Bouvier, a physician-scientist with extensive experience in the transmission of influenza viruses among guinea pigs; Dr. William Ristenpart, an engineer with expertise in the application of high-speed imaging technologies to investigations of complex fluid dynamics; and Dr. Anthony Wexler, an authority on aerosol transport who has developed novel techniques for high-resolution imaging of aerosol deposition in the rodent respiratory tract. Our preliminary theoretical modeling has generated innovative interpretations of the experimental data, yielding three testable hypotheses, which form the basis of this proposal: (1) Influenza virus transmission probability will decrease with increased airflow speed, (2) transmission probability will decrease with the degree of turbulence, and (3) transmission probability will increase with the time integral of the viral concentration within the inoculated animal. Rigorously controlled laboratory studies, designed to isolate a single variable for analysis while others are held constant, will provide a quantitative framework for understanding the cumulative effects of temperature, humidity, airflow velocity, turbulence, and position on the transmission of human influenza viruses in a relevant animal model. Quantifying these environmental variables, individually and cumulatively, will enable their extrapolation to larger environments and time scales, with the potential to transform our understanding of the epidemiology of seasonal and pandemic influenza.