COVID-19 Data Visualization through Automatic Phase Detection

Abstract

This article presents a new interactive visualization system to represent and compare rate of spread of COVID-19 pandemic across different countries over time. We surveyed existing visualization techniques used in various websites and media outlets and introduced use of a knee detection algorithm that divides the exponential spread in multiple linear components. A set of use cases demonstrates the utility of the system in comparing the spread across different countries for both analysis and prediction.