Panviz 2.0: AI-driven visual analytics to adapt to the novel challenges of COVID-19

The ongoing and evolving COVID-19 pandemic has resulted in tremendous negative effects on people's daily lives. It is critical for decision makers such as health care officials and governors to foresee potential impacts and make timely decisions. We present PanViz 2.0, a visual analytics application that combines an epidemic model and AI-driven analytics to infer the best-fit parameters to enable the adaptation to ongoing pandemics at multiple spatial aggregations (nation wide, state level, and county level). Our experiments for predicting the fatality cases in each county of the state of Oklahoma demonstrate the flexibility of our application in adapting to various scenarios and regions. © 2021 IEEE Computer Society. All rights reserved.