Quantifying Environmental Variables Affecting Airborne Influenza Transmission

量化影响空气传播流感传播的环境变量

• 批准号: 8963425
• 负责人: Nicole M. Bouvier
• 金额: $ 39.43万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-11-05 至 2019-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8963425
• 关键词: Address; Aerosols; Affect; Air; Animal Model; Animals; Blood Circulation; California; Cavia; Climate; Complex; Data; Data Set; Dependence; Deposition; Disease Outbreaks; Dryness; Engineering; Environment; Epidemiology; Exhalation; Goals; Health; Housing; Human; Humidity; Image; Imaging technology; Individual; Influenza; Investigation; Laboratories; Laboratory Study; Liquid substance; Mechanics; Modeling; Physicians; Physiology; Population; Positioning Attribute; Precipitation; Probability; Production; Public Health; Research; Research Design; Research Personnel; Resolution; Respiratory System; Respiratory tract structure; Risk; Rodent; Science; Scientist; Site; Social Behavior; Source; Speed; System; Techniques; Temperature; Theoretical model; Time; Universities; Viral; Viral Load result; Virus; Work; authority; base; design; experience; flu transmission; health economics; improved; in vivo; influenzavirus; innovation; laboratory experiment; medical schools; novel; pandemic influenza; particle; physical science; public health intervention; research study; respiratory; respiratory virus; seasonal influenza; skills; therapy design; transmission process; viral transmission; virology

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.

描述（由申请人提供）：量化影响空气流感传播的环境变量在大多数温带气候中，流感在寒冷干燥的冬季流行。然而，在一些温带和热带地区，流感的危险性与极端降水有关，而不是干燥，并且基本上可以在低水平上传播 全年或出现在单一或双模式的年度爆发。环境变量如何影响流感在人群中的传播仍然知之甚少，部分原因是空气传播呼吸道病毒传播背后的科学跨越了生物医学和物理科学之间的学科界限，涵盖了病毒学，生理学，流行病学，流体力学，气溶胶科学和气候学等不同领域。在这里，我们试图了解如何个别环境变量-如温度，湿度和气流-累积影响流感病毒的传播概率在一个代表性的哺乳动物实验系统。这些研究背后的理论框架是一种新的定量模型，该模型基于在实验豚鼠中收集的数据，试图描述环境对感染和易感宿主之间流感病毒传播的影响。该项目弥合了病毒学和工程学之间的差距，汇集了三名具有相关和互补技能的共同研究者：Nicole Bouvier博士，一名在豚鼠中传播流感病毒方面具有丰富经验的医学科学家; William Ristenpart博士，一名在高速成像技术应用于复杂流体动力学研究方面具有专长的工程师;以及安东尼·韦克斯勒博士，他是气溶胶传输方面的权威，开发了啮齿动物呼吸道气溶胶沉积的高分辨率成像新技术。我们的初步理论模型产生了对实验数据的创新解释，产生了三个可检验的假设，这些假设构成了本提案的基础：（1）流感病毒传播概率将随着气流速度的增加而降低，（2）传播概率将随着湍流程度的增加而降低，（3）传播概率将随着接种动物体内病毒浓度的时间积分而增加。严格控制的实验室研究，旨在隔离一个单一的变量进行分析，而其他保持不变，将提供一个定量的框架，了解温度，湿度，气流速度，湍流和位置的累积效应对人类流感病毒在相关动物模型中的传播。量化这些环境变量，单独和累积，将使其外推到更大的环境和时间尺度，有可能改变我们对季节性流感和大流行性流感的流行病学的理解。