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

合作研究：利用新技术预测有毒实体出现的全国研讨会（预防）

• 批准号: 2115122
• 负责人: Paul Torrens
• 金额: $ 2.64万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2115122&HistoricalAwards=false
• 关键词: Collaborative; Research; National; Symposium; PRedicting

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.

在过去的一年里，持续的 COVID-19 大流行严重扰乱了地球上人类的生计，感染了超过 8500 万人，并导致近 200 万人死亡。可以采取哪些行动来最大程度地减轻这种大流行的严重程度（以及可以采取哪些行动）。回想起来，许多行动本可以发挥关键作用：对潜在的动物到人类的感染溢出进行环境监测，建立快速开发疫苗和优化部署的渠道。和分发、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、设计和安排有效的干预措施、培训易感人群采取抑制传染源传播所需的措施，等等。我们的知识、方法、技术和政策方面还存在哪些差距？研究人员提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），以开始应对这些及相关挑战。总体而言，高度跨学科的组织团队在本次研讨会所涉及主题的各个方面都拥有丰富的经验，弥合已知（甚至可能是可知）方面的基本差距可能需要的协调远远超出了共享工具和标准化的范围。 ，或方法和数据的交流；这些更广泛的定义了大流行预测之外的复杂问题的社会挑战，这次会议将有助于协调团队科学工作，有助于将不同的群体聚集在一起，无论是小团队还是大团队，包括将不同的群体聚集在一起。作为公民科学家在公众中。关键在促进流行病预防的预测情报的融合方面，将以跨学科整合的方式共同设想计算、科学和工程，以便社区的努力最适合（并能够灵活地）应对和预防新的流行病。围绕四个主题和观点进行组织：分子、生理学、人口/流行病学和终端/多尺度。拟议的会议将为社区提供一个宝贵的机会来开始建立必要的基础。全体会议、简短演讲、小组讨论和小型突破性思考会议的结合将有助于实现这些目标，出于几个重要原因，大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。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

National Symposium on PRedicting Emergence of Virulent Entities by Novel Technologies (PREVENT)". NSF Predictive Intelligence for Pandemic Prevention (PIPP) Workshop Summary Report. Atlanta, GA: Georgia Tech. 52 pages.

通过新技术预测有毒实体出现的全国研讨会（预防）”。美国国家科学基金会流行病预防预测情报 (PIPP) 研讨会总结报告。亚特兰大，佐治亚州：佐治亚理工学院。52 页。

• 发表时间: 2021-01
• 期刊: National Symposium on PRedicting Emergence of Virulent Entities by Novel Technologies (PREVENT
• 作者: Prakash, B.A.;Torrens, P.M.;Wigginton, K.;Yin, J.
• 通讯作者: Yin, J.