论文标题
部分可观测时空混沌系统的无模型预测
Visualising spatio-temporal health data: the importance of capturing the 4th dimension
论文作者
论文摘要
面对迅速发展的健康威胁，例如传染病爆发，决策者不仅能够不仅在太空中而且在第四维度，时间，而且时间都可以理解复杂的动态。在本文中，这是通过一种新颖的可视化工具来解决的，该工具被称为动态健康Atlas Web应用程序，该应用专门旨在显示随着时间的推移数据的空间演变，同时承认其不确定性。这是一个交互式和开源的Web应用程序，主要在JavaScript中进行编码，其中地理空间和时间数据并排显示。该可视化工具的两个案例研究中的第一个涉及英国犬胃疾病的爆发，那里的许多兽医实践经历了异常高的病例发病率。第二项研究涉及预测的Covid-19-19繁殖编号，以及英国每个地方当局地区的发病率和流行预测。这些研究证明了动态健康Atlas Web应用程序在传达地理空间和时间动态及其相应的不确定性方面的有效性。
Confronted by a rapidly evolving health threat, such as an infectious disease outbreak, it is essential that decision-makers are able to comprehend the complex dynamics not just in space but also in the 4th dimension, time. In this paper this is addressed by a novel visualisation tool, referred to as the Dynamic Health Atlas web app, which is designed specifically for displaying the spatial evolution of data over time while simultaneously acknowledging its uncertainty. It is an interactive and open-source web app, coded predominantly in JavaScript, in which the geospatial and temporal data are displayed side-by-side. The first of two case studies of this visualisation tool relates to an outbreak of canine gastroenteric disease in the United Kingdom, where many veterinary practices experienced an unusually high case incidence. The second study concerns the predicted COVID-19 reproduction number along with incidence and prevalence forecasts in each local authority district in the United Kingdom. These studies demonstrate the effectiveness of the Dynamic Health Atlas web app at conveying geospatial and temporal dynamics along with their corresponding uncertainties.
