PIPP Phase I: Coupling Predictive Intelligence with Adaptive Response to Create Pandemic-Resilient Cities

PIPP 第一阶段：将预测智能与适应性响应相结合，创建具有抗疫能力的城市

• 批准号: 2200338
• 负责人: Benjamin Dalziel
• 金额: $ 100万
• 依托单位: Oregon State University
• 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: 2022-09-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2200338&HistoricalAwards=false
• 关键词: PIPP; Phase; Coupling; Predictive; Intelligence

When the first cases of COVID-19 appeared in cities across the United States, it triggered a process of exponential spread that could not be reversed using available technologies, interventions, and solutions. As climate change accelerates the emergence of pathogens with pandemic potential, cities and urban areas will provide the media and conduits that collect and transmit novel pathogens. Recent advances in pathogen sensing/surveillance and epidemiological forecasting along with the early success in the use of non-pharmaceutical interventions to reduce the spread of COVID-19 suggest that feedback loops between predictive intelligence and adaptive response could enable cities to efficiently attenuate pandemic threats if the feedback is sufficiently localized and rapid. The overarching goal of this project is to lay the foundation for the establishment of a Center that will combine and integrate mathematical/computational modelling with engineering, public health, and public engagement to explore the design and prototyping of city-scale feedback loops that could proactively attenuate the rates of transmission of pathogens with pandemic potential. The proposed PIPP Phase I Center development activities will include targeted research projects, workshops, and workforce development including the mentoring of four graduate students and the establishment of a graduate student rotation program at Oregon State University that will provide cross-training in transdisciplinary pandemic science and enable the development and facilitation of bi-directional trainings and exchanges on pandemic dynamics between scientists, engineers, and public health professionals and stakeholders.This PIPP Phase I project will lay the foundation for a Center that addresses the “Grand Challenge” of transforming cities from pandemic amplifiers to attenuators. To advance this goal, the project team proposes to design, build, and evaluate feedback loops between predictive intelligence and adaptive response that could attenuate pandemic threats in cities and urban areas by leveraging the networks of interacting components in urban systems. The specific objectives of the research are to: 1) Build and scale up community-academic partnerships with public health professionals and community leaders to advance pandemic predictive intelligence and adaptive response in cities and urban areas; 2) Develop mathematical and computational models that could simulate the process of stepping back across epidemic tipping points in urban systems; and 3) Design and prototype feedback loops that could predict and attenuate the transmission of infectious diseases in cities and urban areas. The successful completion of the proposed research has the potential for transformative impact through the establishment of community-academic partnerships to develop and validate disease contagion prediction-response systems and evaluate their effectiveness and adoptability. 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.

当第一批COVID-19病例出现在美国各地的城市时，它引发了一个指数传播的过程，使用现有的技术，干预措施和解决方案无法逆转。随着气候变化加速具有大流行潜力的病原体的出现，城市和城市地区将提供收集和传播新病原体的媒介和渠道。病原体感知/监测和流行病学预测的最新进展沿着使用非药物干预措施减少COVID-19传播的早期成功，表明预测智能和适应性反应之间的反馈回路可以使城市有效地减轻流行病威胁，如果反馈足够本地化和快速。该项目的总体目标是为建立一个中心奠定基础，该中心将联合收割机和数学/计算建模与工程、公共卫生和公众参与相结合，以探索城市规模反馈回路的设计和原型，从而主动降低具有大流行潜力的病原体的传播率。拟议的PIPP第一阶段中心发展活动将包括有针对性的研究项目、讲习班和劳动力发展，包括指导四名研究生，并在俄勒冈州州立大学建立一个研究生轮换计划，该计划将提供跨学科流行病科学方面的交叉培训，并促进科学家、工程师、PIPP第一阶段项目将为一个中心奠定基础，该中心将应对将城市从大流行放大器转变为衰减器的“重大挑战”。为了推进这一目标，项目团队建议设计，构建和评估预测智能和适应性反应之间的反馈回路，通过利用城市系统中相互作用的组件网络来减轻城市和城市地区的流行病威胁。该研究的具体目标是：1）与公共卫生专业人员和社区领导人建立并扩大社区-学术伙伴关系，以促进城市和城市地区的流行病预测情报和适应性反应; 2）开发数学和计算模型，模拟城市系统中跨越流行病临界点的过程; 3）设计和原型反馈回路，可以预测和减少传染病在城市和城市地区的传播。成功完成拟议的研究有可能通过建立社区-学术伙伴关系产生变革性影响，以开发和验证疾病传染预测-反应系统，并评估其有效性和可采用性。该奖项得到了跨部门的大流行预防阶段预测情报（PIPP）计划的支持，该计划由生物科学（BIO），计算机信息科学与工程（CISE），工程（ENG）和社会部门共同资助。行为与经济科学（SBE）该奖项反映了NSF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。