Collaborative Research: National Symposium on PRedicting Emergence of Virulent Entities by Novel Technologies (PREVENT)

过去一年，持续的COVID-19大流行严重破坏了地球上人类的生计，感染了8500多万人，造成近200万人死亡。本可以采取哪些措施来将这次大流行（以及过去几十年之前的其他大流行，如寨卡病毒、SARS和埃博拉病毒）的严重程度降到最低？回想起来，许多行动都可能起到关键作用：对潜在的动物对人类感染溢出进行环境监测，为快速疫苗开发和最佳部署和分发建立管道，设计数据科学工具以准确预测轨迹，快速和适应性综合征监测和行为跟踪，设计和确定有效干预措施的时机，培训易感个体采取必要措施以抑制传染原的传播，等等。我们吸取了哪些教训，在知识、方法、技术和政策方面还存在哪些差距？研究人员建议召开为期两天的多学科全国研讨会，通过新技术预测有毒实体的出现（预防），开始解决这些和相关的挑战。作为一个整体，高度跨学科的组织团队在本次研讨会所涉及的主题的各个方面都有丰富的经验。弥合已知（甚至可能是可知）方面的根本差距可能需要远远超出工具共享、标准化或方法和数据交换的协调；这些定义了大流行预测之外的更广泛的复杂问题的社会挑战。这次会议将有助于实现协调的团队科学工作，可以帮助将不同的团队聚集在一起，无论是小团队还是大团队，包括将公众作为公民科学家引入。促进大流行病预防预测情报的融合的关键将是以跨学科整合的方式共同设想计算、科学和工程，以便社区努力最适合（并能够灵活地）应对和预防新的大流行病。研讨会围绕四个主题和观点展开：分子、生理、人口/流行病学和终端/多尺度。提议的会议将为社区开始建立必要的融合提供一个宝贵的机会。将采用全体会议、简短会谈、小组讨论和小型分组思考会议的组合来帮助实现这些目标。由于几个重要的原因，流行病预防的预测智能将受益于融合计算、科学和工程见解以及传统学科专业知识库。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。

In the past year, the ongoing COVID-19 pandemic has severely disrupted the livelihoods of our planet’s human inhabitants, infecting over 85 million individuals, and causing nearly 2 million deaths. What actions might have been taken to minimize the severity of this pandemic (and others before it in the past decades such as Zika, SARS and Ebola)? In retrospect, many actions could have played key roles: environmental monitoring for potential animal-to-human infection spillovers, establishment of pipelines for rapid vaccine development and optimal deployment and distribution, designing data-science tools to accurately forecast trajectories, fast and adaptive syndromic surveillance and behavior tracking, designing and timing effective interventions, training susceptible individuals for measures needed to inhibit the spread of infectious agents, and others. What lessons have been learned and what gaps in our knowledge, methodologies, technologies, and policies remain? The investigators propose a two-day multi-disciplinary National Symposium on PRedicting Emergence of Virulent Entities by Novel Technologies (PREVENT) to begin to address these and related challenges. As a whole the highly interdisciplinary organizing team has significant experience in various aspects of the topics touched upon by this symposium. Bridging fundamental gaps in what is known (and perhaps even what is knowable) can require coordination that goes far beyond sharing of instruments, standardization, or the exchange of methods and data; these define broader societal challenges of complex problems beyond pandemic prediction. This meeting will help enable coordinated team-science efforts that can assist in bringing disparate groups together, whether in small teams or large teams, including bringing in the public as citizen scientists.Key in fostering convergence for predictive intelligence for pandemic prevention will be co-envisioning computing, science and engineering in ways that are integrated across disciplines so that community efforts are optimally suited to (and nimbly able to) respond to and prevent new pandemics. The symposium has been structured around four themes and perspectives: Molecular, Physiological, Population/Epidemiological and End-end/Multi-scale. The proposed meeting will provide a valuable opportunity for the community to begin to build the necessary convergence. A combination of plenary talks, short talks, panel discussions and small breakout thought sessions will be used to help achieve these aims. For several significant reasons, predictive intelligence for pandemic prevention stands to benefit by drawing upon convergent computation, science and engineering insights alongside traditional disciplinary repositories of expertise.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.