COVID-19联合大流行建模与分析平台

Gautam S. Thakur, Kevin A. Sparks, A. Berres, Varisara Tansakul, S. Chinthavali, M. Whitehead, Erik Schmidt, Haowen Xu, Junchuan Fan, Dustin Spears, Elton Cranfill
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引用次数: 14

摘要

减少COVID-19影响和传播的非药物干预措施需要通过政府、学术界、医学界和公民之间的合作努力制定政策和指导。为了实现这一努力,我们开发了一个全方位的态势感知平台,可以处理多模式和多来源的数据,从而做出明智的决策。除了显示当前感染的传播情况外,该平台还捕获了人类动态对感染传播、关键基础设施的位置和可用性、预测和高性能计算驱动的模拟的影响。该平台是可扩展的,允许第三方集成和服务以近乎实时的方式使用精心策划的数据和分析。我们相信,该平台将加强关键决策,以减少大流行的影响和传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID-19 Joint Pandemic Modeling and Analysis Platform
The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.
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