A Real Time and Interactive Web-Based Platform for Visualizing and Analyzing COVID-19 in Canada

Dan Liu, Yuan Du, Yasin Khadem Charvadeh, Jingyu Cui, Li-Pang Chen, Gansen Deng, Qihuang Zhang, Kaida Cai, Joy He, Wenqing He and Grace Y. Yi

International Journal of Statistics and Probability, 2020, vol. 9, issue 5, 23

Abstract: In the midst of the global outbreak with over 300,000 worldwide death cases of COVID-19, Canada has reported 79,101 confirmed cases of the novel coronavirus (COVID-19) as of May 19, 2020, in which the severity differs from region to region. To provide a timely view and understanding of the evolving pandemic in Canada, we develop a real time interactive web-based platform which primarily includes data visualization and statistical analysis. The website highlights real time tracking of the development of COVID-19 with visualized graphs and forecasts future trends with applications of different statistical predictive models. By providing research-based statistical analysis, we are able to shed the light on the epidemiological characteristics of COVID-19. We also provide timely social news and preventive measures from the government on the website.

Date: 2020
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