PIPP Phase 1: International Center for Avian Influenza Pandemic Prediction and Prevention

PIPP 第一阶段：国际禽流感大流行预测和预防中心

• 批准号: 2200310
• 负责人: Xiangming Xiao
• 金额: $ 100万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2200310&HistoricalAwards=false
• 关键词: PIPP; Phase; International; Center; Avian

Avian influenza, often referred to as bird flu, has had many outbreaks in Asia, Africa, Europe, and North America in the past decades, resulting in losses of billions of poultry, thousands of wild waterfowl, and hundreds of humans. As the 1918 Influenza Pandemic revealed the potential of influenza viruses that originate in birds to kill millions of humans, prediction and prevention of the next influenza pandemic is one of the grand challenges in global health. Although significant investment and research have been made in avian influenza virus (AIV) research over the past two decades, the capacity to predict AIV pandemic is still woefully inadequate. There is an urgent and imperative need to fortify the prediction capacity, as AIV risk factors in the human-animal-environment systems (HAES) have changed rapidly in the past few decades and are expected to change at a much faster pace across the world in the next few decades. This Predictive Intelligence for Pandemic Prevention (PIPP) Phase I: Development Grant assembles a multi-institutional team to explore the appropriate pathways for establishing an International Center for Avian Influenza Pandemic Prediction and Prevention (ICAIP3). The mission of the center is to tackle the grand challenges in global health with a focus on avian-influenza pandemic prediction and prevention. The broader impacts of this project include increased international partnerships between researchers, stakeholders, and decision makers; development of STEM workforce for international and convergent research and diverse career paths; increased public scientific literacy and public engagement; and increased capacity for avian influenza pandemic prediction and prevention. Scientifically, this project focuses on four major problems in pandemic prediction and prevention. First, this project investigates the complex and dynamic data problem via the OneHealth (Human-Animal-Environmental Health) approach and the Big Data approach. Researchers review and assess diverse AIV and HAES datasets and identify the pathways and procedures for harnessing the disparate datasets into analysis-ready datasets for modeling and analysis. Second, this project tackles the multi-scale and interwoven model problem via the integrated modeling approach. Researchers review and assess various AIV models and artificial intelligence (AI) and machine learning (ML) algorithms, and then identify appropriate AIV models and AI/ML algorithms for developing new integrated models to predict AIV evolution, spillover, and transmission. Third, this project assesses the decision support system problem via the structure decision making approach. Researchers review and assess various AIV decision support systems and tools (DSST), and then identify appropriate AIV DSST for further development and practical use in the AIV surveillance, pandemic preparedness, and response. Finally, this project identifies appropriate pathways to develop cyberinfrastructure for data-intensive research, communication, and sharing among the community of zoonotic infectious diseases. The center will be focused on prediction and prevention of AIV pandemic in Eurasia and its potential linkage and risk with North America.This award is supported by the cross-directorate Predictive Intelligence for Pandemic Prevention Phase I (PIPP) program, which is jointly funded by the Directorates for Biological Sciences (BIO), Computer Information Science and Engineering (CISE), Engineering (ENG) and Social, Behavioral and Economic Sciences (SBE).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.

禽流感，通常被称为禽流感，在过去的几十年里在亚洲、非洲、欧洲和北美多次爆发，导致数十亿只家禽、数千只野生水禽和数百人死亡。由于1918年流感大流行揭示了源自禽类的流感病毒可能导致数百万人死亡，因此预测和预防下一次流感大流行是全球卫生领域的重大挑战之一。尽管在过去的二十年里，在禽流感病毒(AIV)的研究方面进行了大量的投资和研究，但预测AIV大流行的能力仍然严重不足。由于人类-动物-环境系统(HAES)中的AIV风险因素在过去几十年中发生了迅速变化，预计在未来几十年中，世界各地的变化速度将更快，因此迫切需要加强预测能力。这一预防大流行的预测性情报(PIPP)第一阶段：发展赠款组建了一个多机构团队，以探索建立国际禽流感大流行预测和预防中心(ICAIP3)的适当途径。该中心的使命是应对全球卫生领域的重大挑战，重点是禽流感大流行的预测和预防。该项目的更广泛影响包括增加研究人员、利益攸关方和决策者之间的国际伙伴关系；为国际和趋同的研究以及多样化的职业道路培养STEM工作人员；提高公众的科学素养和公众参与度；以及提高预测和预防禽流感大流行的能力。科学地讲，这个项目聚焦于大流行预测和预防的四个主要问题。首先，本项目通过OneHealth(人-动物-环境健康)方法和大数据方法调查复杂和动态的数据问题。研究人员审查和评估不同的AIV和HAES数据集，并确定将不同的数据集转化为可供分析的数据集以进行建模和分析的途径和程序。其次，本项目通过集成建模的方法解决了多尺度、交织的模型问题。研究人员回顾和评估各种AIV模型以及人工智能(AI)和机器学习(ML)算法，然后确定合适的AIV模型和AI/ML算法，以开发新的集成模型来预测AIV的进化、溢出和传播。第三，本项目通过结构化决策方法对决策支持系统问题进行评估。研究人员回顾和评估各种AIV决策支持系统和工具，然后确定适当的AIV决策支持系统和工具，以便进一步开发和实际应用于AIV监测、大流行准备和应对。最后，该项目确定了发展网络基础设施的适当途径，以便在人畜共患传染病社区之间进行数据密集型研究、交流和共享。该中心将专注于对欧亚大陆禽流感大流行的预测和预防，及其与北美的潜在联系和风险。该奖项由跨部门大流行预防第一阶段预测情报(PIPP)计划支持，该计划由生物科学(BIO)、计算机信息科学和工程(CESE)、工程(ENG)和社会、行为和经济科学(SBE)主管共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Rapid and large changes in coastal wetland structure in China's four major river deltas

• DOI: 10.1111/gcb.16583
• 发表时间: 2023-01
• 期刊: Global Change Biology
• 影响因子: 11.6
• 作者: Xinxin Wang;Xiangming Xiao;Xi Zhang;Jihua Wu;Bo Li

The changing dynamics of highly pathogenic avian influenza H5N1: Next steps for management & science in North America

• DOI: 10.1016/j.biocon.2023.110041
• 发表时间: 2023-04-28
• 期刊: BIOLOGICAL CONSERVATION
• 影响因子: 5.9
• 作者: Harvey, Johanna A.;Mullinax, Jennifer M.;Prosser, Diann J.
• 通讯作者: Prosser, Diann J.

Potential Effects of Habitat Change on Migratory Bird Movements and Avian Influenza Transmission in the East Asian-Australasian Flyway

• DOI: 10.3390/d15050601
• 发表时间: 2023-04
• 期刊: Diversity
• 作者: J. Takekawa;D. Prosser;Jeffery D. Sullivan;Shenglai Yin;Xinxin Wang;Geli Zhang;Xiangming Xiao