Better Communication of COVID-19 Trends through 3D Visualization

地区政府鼓励全体加拿大人大幅改变日常生活方式，以控制新冠肺炎病毒的传播。然而，传达此类措施的必要性是一项挑战，因为这些变化对人们的生活产生了巨大影响。因此，必须让社区了解地区政府为什么要采取这些措施，这需要研究人员、加拿大和省政府、卫生当局和公众之间更好和有效的沟通。然而，新冠肺炎案例的迅速增加和千差万别的变化给以一种通俗易懂的方式传达信息带来了挑战。可视化这类数据的具体挑战是，许多潜在的趋势本质上是指数性的。向公众解释这种趋势是具有挑战性的；人们可能没有注意到线性可视化和对数可视化之间的根本区别，以显示病例的数量，或者他们可能没有正确地解释数据。因此，需要针对新冠肺炎趋势进行简单、有效和易于理解的数据可视化，使公众能够了解并关注形势的重要性。此外，我们不知道之前关于普通民众对新冠肺炎数据可视化的反应的工作，我们需要找出在这种背景下吸引人们注意的好方法。在这个项目中，我们计划调查人们对现有的新冠肺炎数据可视化方法的反应，以及他们的反应在新的可视化方法和技术下发生了怎样的变化。我们建议使用新的3D可视化方法，并比较2D和3D可视化方法对人群的新冠肺炎数据的影响。通过将所有这些研究成果应用到包括虚拟、增强、混合现实在内的不同平台上，我们希望增加新冠肺炎传播的有效性。有了这种沟通，就更容易鼓励民众遵守戴口罩等措施，并继续限制集会的规模。

The whole Canadian population was encouraged by regional governments to change their daily lifestyle significantly to control the spread of the COVID-19 virus. Yet, communicating the need for such measures is a challenge, because these changes have an enormous impact on people's lives. Thus, the community has to be informed about why regional governments are taking these measures, which requires better and effective communication between researchers, the Canadian and provincial governments, health authorities, and the public. However, the rapid increase and widely varying change in COVID-19 cases makes it challenging to convey the messages in a way that is easy to understand. The specific challenge in visualizing such data is that many of the underlying trends are exponential in nature. Explaining such trends to the general public is challenging; people may not notice the fundamental difference between linear and logarithmic visualizations to show the number of cases, or they might not interpret the data correctly. Thus, there is a need for simple, effective, and easy-to-understand data visualization for COVID-19 trends, which enables the public to understand and focus on the importance of the situation. Also, we are not aware on previous work on the response of the general population to COVID-19 data visualizations, and we need to identify good approaches to attract people's attention for this context. In this project, we are planning to investigate how people respond to existing COVID-19 data visualization methods and how their reaction changes with novel visualization methods and techniques. We propose to use novel 3D visualisation approaches and to also compare the impact of 2D and 3D visualisation methods to visualize COVID-19 data on the population. By applying all these research outcomes to application on different platforms, including Virtual, Augmented, Mixed Reality, we want to increase the effectiveness of COVID-19 communication. With such communication, it will be easier to encourage the population to comply with measures, such as wearing facemasks and to continue to limit the size of gatherings.