PIPP Phase I: Center for Pandemic Decision Science - Developing Robust Paradigms for Anticipating and Mitigating Uncertain Pathogen Threats

尽管几十年来一直在努力防范大流行，但COVID-19还是让世界大吃一惊。国家和全球卫生界没有预见到与绘制潜在威胁生态系统、阐明相互依存的行为和政治动态以及为决策者提供灵活的科学、战略和培训相关的挑战的范围。该项目设想了一个应对病原体威胁的更充分准备的未来，旨在为流行病决策科学中心奠定基础，该中心将打破学术界、政府和行业机构之间长期存在的隔阂，这些机构共同指导大流行的防范和应对工作，但并不总是相互协作。在接下来的18个月里，一个由来自10个机构的35名自然科学家、社会科学家、计算机科学家、工程师、医生和公共卫生官员组成的团队将主持一系列跨学科研讨会，并开展试点研究，为解决三个基本研究问题奠定知识和组织基础——我们如何预测潜在病原体威胁的巨大宇宙并从源头发现它们？人们、社区和领导人将如何应对新出现的威胁？我们如何将科学融入准备、遏制和应对范围内的决策？对于这些问题中的每一个，该团队将确定基础研究、科学家和决策者培训以及预测智能能力开发的近期和长期目标。这些活动将建立一个以复杂系统建模为基础的新的研究范式，整合不同学科的观点和方法，并与决策者广泛接触，以确保科学既相关又实用。该项目将通过研讨会和座谈会广泛吸引研究界和公共卫生界参与，培训多样化的学生群体，开发大流行决策科学的本科教学模块，并通过在线平台、媒体和同行评审出版物传播由此产生的见解和产品。在2019冠状病毒病大流行期间，这个由科学家、工程师、社会科学家和临床医生组成的跨学科团队一直在开发数学模型，为从地方到全球各个层面的决策者提供态势感知、可操作的预测和时效性政策分析。该团队与政府机构、医疗保健系统和学校密切合作，随着病毒、人类行为反应和有效对策的不断变化，提供预测性情报。这项工作阐明了三个相互关联的重大挑战。第一个是全球在预测新型病原体威胁方面的想象力失败，尽管几十年来进行了协调一致的防范工作。第二是根本无法预测个人、集体和政府在威胁期间的行为反应。第三个问题是科学与个人、机构和决策者做出的决定之间持续存在的差距。该项目将启动一个流行病决策科学中心，通过推进复杂系统科学与流行病决策的整合来应对这些重大挑战。作为第一步，该中心将开展一系列包容性的多学科研讨会和试点研究，以促进创新的跨学科研究，包括新威胁的出现和检测、人们行为的动态，以及设计和采用自适应决策范式，以预防、跟踪和减轻不确定性下的病原体威胁。这些活动将磨练中心的愿景，确定关键的研究重点，并着手开展多样化的教育和社区建设活动组合，以推进病原体防范的科学和实践。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）、社会、行为和经济科学（SBE）和工程（ENG）委员会联合资助。该项目还与美国疾病控制与预防中心合作资助，以支持进一步提高联邦传染病建模、预防和应对能力的研究项目。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。

Despite decades of pandemic preparedness efforts, COVID-19 took the world by surprise. The national and global health community did not foresee the extend of challenges associated with charting ecosystems of potential threats, elucidating interdependent behavioral and political dynamics, and equipping decision makers with nimble science, strategies, and training. This project imagines a better prepared future for responding to pathogen threats and aims to build the basis for a Center for Pandemic Decision Science that will break down the persistent silos separating the academic, government, and industry institutions that have collectively, but not always collaboratively, guided pandemic preparedness and response efforts. Over the next 18 months, a team of 35 natural scientists, social scientists, computer scientists, engineers, physicians, and public health officials from 10 institutions will host a series of interdisciplinary workshops and undertake pilot studies that will lay the intellectual and organizational groundwork for tackling three fundamental research questions - How can we anticipate the vast universe of potential pathogen threats and detect them at their source? How will people, communities, and leaders behave and respond to emerging threats? How can we integrate science into decision making across the preparedness, containment, and response spectrum? For each of these questions, the team will identify immediate and long-term goals for basic research, training of scientists and decision makers, and development of predictive intelligence capabilities. These activities will establish a new research paradigm that is grounded in complex systems modeling, integrate perspectives and methods across diverse disciplines, and engage extensively with decision makers to ensure that the science is both relevant and practical. The project will broadly engage the research and public health communities through workshops and colloquia, train a diverse group of students, develop an undergraduate teaching module in pandemic decision science, and disseminate resulting insights and products through online platforms, media, and peer-reviewed publications. Throughout the COVID-19 pandemic, this interdisciplinary team of scientists, engineers, social scientists, and clinicians has been developing mathematical models to provide situational awareness, actionable forecasts, and time-sensitive policy analyses for decision makers on all scales, from local to global. The team has partnered closely with government agencies, healthcare systems, and schools to provide predictive intelligence as the virus, human behavioral responses, and the arsenal of effective countermeasures continually shifted. This work has elucidated three interlinked grand challenges. The first is the global failure of imagination in anticipating novel pathogen threats, despite decades of concerted preparedness efforts. The second is the fundamental inability to anticipate individual, collective, and governmental behavioral responses during the threats. The third is the persistent gap between science and the decisions made by individuals, agencies, and policymakers. This project will launch a Center for Pandemic Decision Science that tackles these grand challenges by advancing the integration of complex systems science into pandemic decision making. As a first step, the Center will conduct a series of inclusive, multidisciplinary workshops and pilot studies that will spur innovative interdisciplinary research into the emergence and detection of novel threats, the dynamics of people’s behavior, and the design and adoption of adaptive decision paradigms for preventing, tracking and mitigating pathogen threats under uncertainty. These activities will hone the Center’s vision, identify key research priorities, and embark on a diverse portfolio of educational and community building activities to advance the science and practice of pathogen preparedness. 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), Social, Behavioral and Economic Sciences (SBE) and Engineering (ENG). This project was also funded in collaboration with the CDC to support research projects to further advance federal infectious disease modeling, prevention and response capabilities.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.