RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19

新冠肺炎疫情的计算模型在英国抗击新冠肺炎的努力中发挥了重要作用。在全国范围内，大约有100个研究团队致力于不同的模型，其中数十个提供了模拟、估计和预测，为四个母国的政府决策提供信息。一个值得注意的疏忽是，可视化和可视化分析技术在支持模型开发的科学工作流程方面利用不足，这通常包括一系列迭代过程，例如(A)假设形成和因果分析；(B)模型开发、测试、验证和比较；(C)模型部署、监测和改进；以及(D)科学和公共传播。由于可视化仅被广泛误认为是信息或知识传播，因此该技术在建模工作流程的所有其他阶段通常未得到充分利用。理想情况下，建模科学家和流行病学家可以在任何需要的时候快速浏览动态数据。股票经纪人观察股票市场数据)，获取疾病发展和控制的时空模式的有效概述(参见，气象学家观察卫星图像、等高线地图等)，提供外部数据存储以刺激假设和考虑各种决策(参见。一位将军在作战室里对着许多地图走来走去)，并从一组分析算法和可视化中接收关于隐藏在数据中的相似性、异常、集群、相关性、因果关系和关联的建议(参见。首席执行官咨询专家)。理想情况下，有一个视觉分析基础设施，作为“常备能力”(国务卿)，可以支持许多建模团队执行日常观察、分析和模型开发任务。拟议的退伍军人管理局技术和知识基础设施对于抗击新冠肺炎大流行至关重要，因为许多流行病学家正在为新冠状病毒10在一段时间内构成威胁做准备。随着最近本地化控制措施的引入，这表明许多当地科学家和医疗保健专业人员需要更多的本地化退伍军人管理局支持。当疫苗接种开始时，需要对不同地区使用的不同疫苗的效力进行监测和建模。这种全国性的需求可以由退伍军人管理局的技术和知识基础设施以成本效益的方式提供。

Computational modelling of the COVID-19 pandemic has been playing a significant role in the UK's effort to combat COVID-19. Across the country, there are about 100 research teams working on different models, and several dozens have provided simulation, estimation, and prediction to inform the governmental decisions in the four home nations. One noticeable oversight is the under-utilisation of visualization and visual analytics technology in supporting the scientific workflows for model development, which typically consists of a set of iterative processes, such as (a) hypothesis formulation and causality analysis; (b) model development, testing, validation, and comparison; (c) model deployment, monitoring, and improvement; and (d) scientific and public dissemination.Because visualization is widely mistaken only for information or knowledge dissemination, the technology is commonly underused in all other stages of a modelling workflow. Ideally, modelling scientists and epidemiologists could have a quick glance of dynamic data anytime there is a need (cf. stock brokers observing stock market data), access effective overviews of spatiotemporal patterns of the disease development and control (cf., meteorologists observing satellite images, contour maps, etc.), be provided with external memorization of data to stimulate hypotheses and contemplate various decisions (cf. a general pacing around in a war room in front of many maps), and receive advice from an ensemble of analytical algorithms and visualizations about similarity, anomalies, clusters, correlation, causality, and association hidden in the data (cf. a CEO consulting specialists). Ideally, there is a visual analytics infrastructure, as a "standing capacity" (Secretary of State), that can support many modelling teams performing daily observational, analytical, and model-developmental tasks.The proposed VA technical and knowledge infrastructures are essential for combating COVID-19 pandemic, as many epidemiologists are preparing for COVID-10 to be a threat for some time. With the recent introduction of localised control measures, it indicates an additional need for localised VA supports for many local scientists and healthcare professionals. When vaccination starts, there is a need for monitoring and modelling the effectiveness of different vaccines used in different regions. Such a nationwide need can be cost-effectively delivered by the VA technical and knowledge infrastructures.