US COVID-19 Spread Analysis/Visualization using Information Theory

STAT 430 final project

Contributed by

• Yashraj Bhosale
• Seung Hyun Kim

How to run

All required dependencies are specified in requirements.txt.

We provide jupyter notebook file covid_raw_data_testing.ipynb to download and visualize correlation data between state-wise case reports.

To further analyze directional causality, use the script:

python analysis.py         # Single-core (debug)
mpirun python analysis.py  # Multi-core

Dash

To visualize data in interactive plotting, you can launch the dash app by:

python app/main.py

Related theories

References

• Schreiber, Thomas., Measuring Information Transfer, 2000, https://journals.aps.org/prl/pdf/10.1103/PhysRevLett.85.461