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.

在过去的几十年中，通常被称为鸟类流感的禽流感，在亚洲，非洲，欧洲和北美发生了许多爆发，导致数十亿家禽，成千上万的野生水禽和数百人的损失。正如1918年的流感大流行所揭示的那样，源自鸟类的流感病毒的潜力杀死了数百万人类，预测和预防下一个流感大流行是全球健康中的巨大挑战之一。尽管在过去的二十年中，对鸟类流感病毒（AIV）研究进行了大量投资和研究，但预测AIV大流行的能力仍然不足。迫切需要强化预测能力，因为在过去的几十年中，人类 - 环境系统（HAES）的AIV风险因素发生了迅速变化，预计在未来几十年中，全球速度会更快地改变。这种大流行预防（PIPP）的预测智能I阶段：发展赠款组装了一个多机构的团队，以探索建立国际禽流感大流行预测与预防中心的适当途径（ICAIP3）。该中心的任务是应对全球健康中的巨大挑战，重点是禽流膜大流行预测和预防。该项目的更广泛影响包括研究人员，利益相关者和决策者之间的国际伙伴关系增加；为国际和融合研究以及各种职业道路的STEM劳动力发展；提高公共科学素养和公众参与；并增加了禽流感大流行预测和预防的能力。从科学上讲，该项目着重于大流行预测和预防的四个主要问题。首先，该项目通过OneHealth（人类 - 环境健康）方法和大数据方法研究了复杂而动态的数据问题。研究人员审查和评估了不同的AIV和HAES数据集，并确定将不同的数据集利用分析就绪的数据集进行建模和分析的途径和程序。其次，该项目通过集成建模方法解决了多尺度和交织的模型问题。研究人员审查和评估各种AIV模型和人工智能（AI）和机器学习（ML）算法，然后确定适当的AIV模型和AI/ML算法，以开发新的集成模型，以预测AIV进化，溢出和传输。第三，该项目通过结构决策方法评估决策支持系统问题。研究人员审查和评估各种AIV决策支持系统和工具（DSST），然后确定适当的AIV DSST，以进一步开发和实际使用，以在AIV监视，大流行准备和反应中进行实际使用。最后，该项目确定了开发网络基础结构的适当途径，用于数据密集型研究，沟通和共享的人畜共患性传染病社区。 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 Sc​​iences (SBE).This奖项反映了NSF的法定任务，并通过使用基金会的智力优点和更广泛的影响审查标准评估值得支持。

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