PIPP Phase I: Center for Emerging Pathogen Prediction and Integration

流行病预防预测情报（PIPP）第一阶段：新兴病原体预测和整合发展资助中心（CEPPI）将领导在不断变化的环境中对野生动物病原体的战略监测。了解和预防新的传染病的出现需要解释许多类型的数据（例如，关于致病病原体的信息、人类和野生动物种群之间的相互作用以及与之相关的环境变化）。该小组将利用博物馆等生物储存库中提供的大量历史数据和样本，系统地调查病原体的出现，从而实现对人畜共患疾病的可靠预测，从而帮助预防或减轻未来的大流行。在世界范围内，特别是在低收入的生物多样性地区，野生动物病原体生物学的许多方面仍然缺乏记录。流行病是一项挑战，需要国际协作和主动解决方案，因此本中心将重点开发培训下一代病原体生物学家的最佳方法，改善生物多样性基础设施、数据库和工作流程，然后在全球分享这些新方法。该中心将特别与美洲的合作博物馆合作，扩大野生动物取样战略，建立一个更全面、更分散的标本库和研究人员网络，以改进病原体的识别和监测。为了改善病原体的检测、监测和缓解，该中心将推广最先进的生物库、基因组筛选和生物信息学工作流程，这些工作流程由直观的交互式可视化网络工具、计算和数学建模以及机器学习提供支持。将病理生物学快速可视化和智能化地整合到庞大的全球野生哺乳动物数字基础设施中，是该中心的基石，该中心将作为流行病预测和预防的早期预警系统。在第一阶段，跨学科团队的目标是开发国际上可扩展的多学科工作流程，以建立：1)从代表哺乳动物群落十年采样的现有档案生物储存库中提取的病原体和宿主的信息学基线，这将直接与改进监测和监测的有针对性战略联系起来；2)简化测序和生物信息学方法的管道，以快速，负担得起，大规模筛选哺乳动物宿主和寄生虫样本，提供可扩展的多样性和随空间和时间变化的观点；3)病原体风险评估，结合结合社会和环境参数和病原体多样性的新方法来预测加速人为变化的结果；4)在地方生物储存库之间开展合作，制定战略性采样和数字化协议，以扩大地理、时间和分类覆盖范围；5)通过教育模块、直接参与和协作学习来解决问题的网络。cepi通过与当地社区、测序和生物信息学设施以及公共卫生和自然资源机构建立新的联系，帮助将病原体和生物多样性的探索标准化。可视化、信息学解释和翻译的新能力源于快速、可负担、可扩展的测序和生物信息学技术的发展。这些能力将激发病原体检测、发现和监测的新方法，从而促进全球病原体监测和缓解。该奖项由流行病预防的跨部门预测情报第一阶段（PIPP）计划提供支持，该计划由生物科学（BIO）、计算机信息科学与工程（CISE）、工程（ENG）和社会、行为和经济科学（SBE）委员会联合资助。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。

The Predictive Intelligence for Pandemic Prevention (PIPP) Phase I: Development Grants Center for Emerging Pathogen Prediction and Integration (CEPPI) will lead strategic surveillance of wildlife pathogens across changing environments. Understanding and preventing the emergence of new infectious diseases requires interpreting many types of data (e.g., information on the disease-causing pathogens, interactions between the human and wildlife populations, and changes in their associated environments). The team will use the vast historical data and sampling available in biorepositories, such as museums, to systematically investigate pathogen emergence to enable reliable predictions of zoonotic disease to help prevent or mitigate future pandemics. Many aspects of pathogen biology in wildlife remain poorly documented worldwide, particularly in low-income, biodiverse regions. Pandemics pose a challenge that requires international, collaborative, proactive solutions, so the Center will focus on developing best methods in training the next generation of pathogen biologists, improving basic biodiversity infrastructure, databases, and workflows, and then sharing these new approaches globally. Working especially with partner museums in the Americas, the Center will expand wildlife sampling strategies to develop a more comprehensive, decentralized network of specimen repositories and researchers to improve pathogen identification and surveillance.To improve pathogen detection, surveillance, and mitigation, the Center will promote state-of-the-art biorepositories, genomic screening, and bioinformatic workflows, which are empowered by intuitively interactive visualization web tools, computational and mathematical modeling, and machine learning. Rapid visual and intelligent integration of pathobiology into the vast global, digital infrastructure for wild mammals is the cornerstone of this Center, which will act as an early warning system for pandemic prediction and prevention. In Phase I, the cross-disciplinary team aims to develop internationally scalable multidisciplinary workflows to build: 1) informatics baselines for pathogens and hosts derived from existing archival biorepositories representing decadal sampling of mammalian communities that will be linked directly to targeted strategies for improved monitoring and surveillance; 2) pipelines that streamline sequencing and bioinformatic methods for rapid, affordable, large-scale screening of mammalian host and parasite samples to provide scalable views of diversity and change over space and time; 3) pathogen risk assessments linking novel methods that integrate social and environmental parameters and pathogen diversity to predict the outcomes of accelerating anthropogenic change; 4) collaborations across local biorepositories to develop strategic sampling and digitization protocols for expanded geographic, temporal and taxonomic coverage; and 5) problem-solving networks through educational modules, direct engagement, and collaborative learning. CEPPI helps standardize exploration of pathogens and biodiversity by building new connections with local communities, sequencing and bioinformatic facilities, and public health and natural resource agencies. New capacities for visualization, informatics interpretation, and translation emanate from the development of fast, affordable, and scalable sequencing and bioinformatic technologies. These capacities will stimulate new methods of pathogen detection, discovery, and monitoring that will foster global pathogen surveillance and mitigation. 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.