US-China Collab: Comparative evolution and ecology of swine influenza viruses in China and the United States

甲型流感病毒是造成大量人类发病率和死亡率的原因，并继续对公共卫生构成巨大挑战。有人提出，猪是中间宿主“混合容器”，通过禽、猪和/或人流感病毒的基因重组产生大流行性流感毒株。尽管在猪群中经常检测到进化事件（即重组和突变），但尚不清楚哪些是典型的，哪些是非典型的，这些流感病毒的哪些进化事件增加了对人类和动物健康的威胁，以及哪些生态和进化原理推动了这些事件。本研究的总体目标是通过组建一个国际和多学科团队，在中国和美国这两个世界上最大的猪肉生产国进行协同研究，开发和应用跨学科方法来研究和比较甲型猪流感病毒的进化和生态。具体而言，该项目将：(1)通过流感监测和先进的进化分析，识别和确定两国猪群中新型猪流感病毒的进化动态；(2)通过地理空间建模和机器学习，确定独特、共同和协同的生态驱动因素；(3)利用大数据和人工智能开发流感风险评估工具。该项目将培养研究生、本科生、兽医和医学生的跨学科研究技能，以研究进化生物学、疾病生态学、流行病学、地理空间建模、大数据和人工智能。通过实习和外展活动，本项目还将对公众和非学术利益相关者进行传染病生态学、进化和传播的教育，这可能会导致养猪业管理的优化和人类行为的改变，从而减少猪流感进化事件、猪群之间的疾病传播以及猪流感病毒对人类的溢出。本研究将阐明导致人畜共患病和大流行风险增加的猪流感病毒的进化动力学，并通过定义流感流行和进化基线来确定非典型进化事件。预计将确定与新型猪流感病毒在猪群中出现和传播以及在动物-人界面相关的生态驱动因素。此外，将采用跨学科方法整合来自两个独特但相互关联的生态环境的数据，以促进对猪群内和动物-人界面甲型流感病毒的进化和生态的全面了解。此外，将开发和共享基于大数据和人工智能的计算工具，以推进将医学、兽医、社会和环境科学联系起来的计算方法，提高我们应对新发和再发传染病的能力。本研究旨在促进我们对流感病毒自然史的了解，并推进流感病毒的生态学理论。这项研究的知识将有助于为流感大流行的防范提供信息和优化政策和对策。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Influenza A viruses are responsible for substantial human morbidity and mortality and continue to present an overwhelming public health challenge. It has been proposed that pigs are intermediate host “mixing vessels” that generate pandemic influenza strains through genetic reassortment among avian, swine, and/or human influenza viruses. Although evolutionary events (i.e., reassortment and mutations) have been routinely detected in swine population, it is not yet clear which are typical, which are atypical, which evolutionary events for these influenza viruses increase threats to human and animal health, and which ecological and evolutionary principals are driving such events. The overall goal of this study is to develop and apply interdisciplinary approaches to study and compare the evolution and ecology of swine influenza A viruses through synergistic studies in China and the US, the two largest pork producing countries on the planet, by assembling an international and multi-disciplinary team. Specifically, this project will 1) identify and determine the evolutionary dynamics of novel swine influenza viruses in swine populations in the two countries through influenza surveillance and advanced evolutionary analyses, 2) determine unique, common, and synergistic ecological drivers through geospatial modeling and machine learning, and 3) develop an influenza risk assessment tool using Big Data and Artificial Intelligence. This project will train graduate, undergraduate, veterinary, and medical students in interdisciplinary research skills for studying evolutionary biology, disease ecology, epidemiology, geospatial modeling, Big Data, and AI. Through internship and outreach activities, this project will also educate the public and non-academic stakeholders on ecology and evolution and transmission of infectious diseases, which may lead to the optimization of swine industry management and changes in human behaviors that could reduce the influenza evolutionary events in pigs, disease transmission among pig populations, and spillover of swine influenza virus to humans.This study will illustrate the evolutionary dynamics of swine influenza viruses leading to enhanced zoonotic and pandemic risk and identify atypical evolutionary events by defining a baseline for influenza prevalence and evolution. It is expected that ecological drivers associated with emergence and spread of novel swine influenza viruses within swine populations and at the animal-human interface will be identified. In addition, data from two unique but linked ecological settings will be integrated using an interdisciplinary approach to facilitate the comprehensive understanding of the evolution and ecology of influenza A viruses within swine populations and at the animal-human interface. Furthermore, Big Data and AI-based computational tools will be developed and shared to advance computational methods linking medical, veterinary, social, and environmental sciences, enhancing our ability to respond to emerging and reemerging infectious diseases. This study aims to facilitate our understanding of the natural history of influenza viruses and advance ecological theories for influenza viruses. The knowledge from this study will help inform and optimize policies and countermeasures for influenza pandemic preparedness.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.