仪表板
大流行
分析
2019年冠状病毒病(COVID-19)
数据科学
视觉分析
可视化
计算机科学
疾病
医学
传染病(医学专业)
数据挖掘
病理
作者
Christopher G. Healey,Susan J. Simmons,Chandra Manivannan,Yoonchul Ro
出处
期刊:Big data
[Mary Ann Liebert]
日期:2022-04-01
卷期号:10 (2): 95-114
被引量:4
标识
DOI:10.1089/big.2021.0023
摘要
The coronavirus disease COVID-19 was first reported in Wuhan, China, on December 31, 2019. The disease has since spread throughout the world, affecting 227.2 million individuals and resulting in 4,672,629 deaths as of September 9, 2021, according to the Johns Hopkins University Center for Systems Science and Engineering. Numerous sources track and report information on the disease, including Johns Hopkins itself, with its well-known Novel Coronavirus Dashboard. We were also interested in providing information on the pandemic. However, rather than duplicating existing resources, we focused on integrating sophisticated data analytics and visualization for region-to-region comparison, trend prediction, and testing and vaccination analysis. Our high-level goal is to provide visualizations of predictive analytics that offer policymakers and the general public insight into the current pandemic state and how it may progress into the future. Data are visualized using a web-based jQuery+Tableau dashboard. The dashboard allows both novice viewers and domain experts to gain useful insights into COVID-19's current and predicted future state for different countries and regions of interest throughout the world.
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