Reinert Audrey, Snyder Luke S, Zhao Jieqiong, Fox Andrew S, Hougen Dean F, Nicholson Charles, Ebert David S
University of Oklahoma.
Purdue University.
Comput Sci Eng. 2020 Sep 14;22(6):48-59. doi: 10.1109/MCSE.2020.3023288. eCollection 2020 Nov.
We introduce a trans-disciplinary collaboration between researchers, healthcare practitioners, and community health partners in the Southwestern U.S. to enable improved management, response, and recovery to our current pandemic and for future health emergencies. Our Center work enables effective and efficient decision-making through interactive, human-guided analytical environments. We discuss our PanViz 2.0 system, a visual analytics application for supporting pandemic preparedness through a tightly coupled epidemiological model and interactive interface. We discuss our framework, current work, and plans to extend the system with exploration of what-if scenarios, interactive machine learning for model parameter inference, and analysis of mitigation strategies to facilitate decision-making during public health crises.
我们介绍了美国西南部研究人员、医疗从业者和社区健康伙伴之间的跨学科合作，以改进对当前大流行以及未来卫生紧急情况的管理、应对和恢复。我们中心的工作通过交互式、人工引导的分析环境实现有效且高效的决策。我们讨论了我们的PanViz 2.0系统，这是一种视觉分析应用程序，通过紧密耦合的流行病学模型和交互式界面来支持大流行防范。我们讨论了我们的框架、当前工作以及扩展该系统的计划，包括探索假设情景、用于模型参数推断的交互式机器学习，以及分析缓解策略以促进公共卫生危机期间的决策。
