PIPP Phase I: Collective Intelligence for Pandemic Prediction Prevention and Response

大流行预防预测情报（PIPP）第一阶段：发展赠款旨在测试一个新平台的可行性和性能，该平台可以合并当前孤立的工具，以改变传染病监测和公共卫生干预。数字平台将是一个不断发展的资源，为四个关键的流行病预防情报领域提供工具包。第一个领域的目标是监测，如接触者追踪（人类互动）和病原体废水检测。第二个领域是诊断，如快速检测疾病。第三个领域是开发分析智能，如知识图谱或预测方法。最后一个领域是行动，如政策和公共卫生建议。作为该平台的一个关键特征，从研究人员和医生到政治家和公众的所有利益相关者都将能够向平台提供数据并从中获取信息。如果成功，这样一个系统将提供关键的科学证据，并成为通过未来的流行病预防预测情报（PIPP）促进进一步公共卫生调查的试验平台该中心将社会科学与以实验室为导向的自然科学相结合，并汇集了跨学科的专业知识。除了研究之外，为准备未来的流行病准备工作队伍的培训和教育社区并将社区纳入流行病预防工作的外展活动将是未来PIPP中心活动的重要组成部分。该项目将通过联合公共卫生执行者，社区和传染病，生物工程，统计建模，公共卫生，计算机科学，以人为本的设计，政策，性别，公平，探索未来PIPP中心的运作框架。项目活动将根据以下目标实施：1）创建一个集体智能网络基础设施原型，并通过真实世界环境中的桌面模拟对其进行测试; 2）使用知识翻译和原型社区互动为未来的PIPP中心生成新的知识，计划和基础设施; 3）为中心的活动和政策制定团队科学方法和以道德为重点的框架，并建立社区和利益相关者的参与，以指导中心的发展。作为发展活动的一部分，开展的协作性跨学科讨论将有助于确定知识差距、研究挑战以及大流行病预防和应对方面的教育和公众参与的新机会。开发活动将产生一个原型集体智慧平台，为有效的人-技术整合以及流行病预测和应对的闭环方法提供重要见解。最后，一个充满道德和以人为本的愿景的关键路线图将被制作并转化为实践，作为将参与式设计，团队科学和网络物理系统开发结合在一起的框架。通过这种从实践中学习的方法，该项目将推进流行病情报科学，并支持教育和培训流行病准备工作人员。该奖项由跨部门的流行病预防预测情报第一阶段（PIPP）计划支持，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）。该奖项反映了NSF的法定使命，并被认为是值得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的支持。

This Predictive Intelligence for Pandemic Prevention (PIPP) Phase I: Development Grant aims to test the feasibility and performance of a new platform that can merge currently siloed tools, in order to transform infectious-disease surveillance and public-health intervention. The digital platform will be an evolving resource that provides the toolkit for four key pandemic-prevention intelligence areas. The first area targets surveillance, such as contact tracing (human interaction) and wastewater detection of pathogens. The second area is diagnosis, such as rapid testing for disease. The third area is developing analytic intelligence, such as knowledge graphs or prediction methods. The final area is action, such as policy and public health recommendations. As a key feature of the platform, all stakeholders from researchers and medical doctors to politicians and the general public will be able to both contribute data to the platform and draw information from it. If successful, such a system would provide critical scientific evidence and become a testbed to foster further public-health investigations via a future Predictive Intelligence for Pandemic Prevention (PIPP) Center that combines social sciences with lab-oriented natural science and brings together expertise from across disciplines. In addition to research, training to prepare a future pandemic-ready workforce and outreach activities that educate and integrate the community into pandemic prevention efforts will be important parts of future PIPP Center activities.This project will advance convergence science for pandemic intelligence by uniting public-health implementers, the community, and experts in infectious disease, bioengineering, statistical modeling, public health, computer science, human-centered design, policy, and gender, equity to explore an operational framework for a future PIPP Center. Project activities will be implemented according to the following objectives: 1) Create a collective intelligence cyberinfrastructure prototype and test it through a tabletop simulation in a real-world setting; 2) Use knowledge translation and prototype-community interaction to generate new knowledge, plans, and infrastructure for a future PIPP center; 3) Develop a team-science approach and ethics-focused framework for Center activities and policies, and build community and stakeholder engagement to guide Center development. The collaborative, interdisciplinary discussions held as part of the development activities will result in the identification of knowledge gaps, research challenges, and new opportunities for education and public engagement regarding pandemic prevention and response. Development activities will result in a prototype collective intelligence platform that will provide important insights into effective human-technology integration and closed-loop methods of pandemic prediction and response. Finally, a critical roadmap imbued with ethics and people-centered vision will be produced and converted to practice as a framework for stitching together participatory design, team science, and cyber-physical system development. Through this practice-to-learn approach, this project will advance the science of pandemic intelligence and support the education and training of a pandemic-ready workforce.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.