ABSTRACT
Federal, state, and local governments have been tracking the spread of the COVID-19 pandemic, an infectious disease caused by a coronavirus. As a result of this pandemic, a consistent stream of health data has been produced that tracks the state of health for the seven billion plus people in the world each day, much of which has been publicly released. This open-source data can be used to analyze, visualize, and explain the spread of COVID-19. Here, a COVID-19 information system was created with the business intelligence software Tableau utilizing big data analysis techniques to contribute to general knowledge about the global pandemic. At a state level, data was collected from the big data initiative, the Covid Tracking Project. At the county level, if not provided in a downloadable format, the data was transcribed into a comma-separated values (CSV) file format and used for analysis. Data collection, cleaning, merging, and filtering was a time consuming and tedious task. The COVID-19 pandemic and increased amount of data collection has highlighted the need to perform rapid data analysis and visualizations. Tableau was used for the rapid prototyping of information system. The available data was decentralized and showed the lack of consistency and lack of nation-wide standardization in collecting COVID-19 data. Uncertainties in the data could be reduced through emphasizing how not all states release the same information, as well as efforts for transparency with how published statistics are calculated. The work aims to draw attention to the need for standardized data collection and the viability of using software such as Tableau for the creation of rapid visualizations. © 2021 ACM.