We utilize socioeconomic, mobility, and epidemiological datasets to forecast COVID-19 cases at the US county/county-equivalent level. This repository contains the code we use to generate this information.
We hope to serve as a valuable resource for understanding trends in the ongoing pandemic and raise awareness about COVID-19 at the community level, something which is desperately needed in our attempts to lower the curve. However, we strongly advise against over-interpreting our predictions. Machine learning models are only as good as the data that trains them. We use the best quality data that is available to us, but we acknowledge that error in our predictions is unavoidable.
Follow these instructions to get the project up and running on your local machine.
These are what you must install before using our project.
Your local machine must also have Python 3 (≥ 3.7) installed beforehand.
To run this project, first clone this repository.
git clone https://github.com/solveforj/pandemic-central.git
For a basic usage, use this command
python covid.py -d
python covid.py --default
This command should download the data from sources, preprocess them, train, and export predictions.
For full list of available commands, use
python covid.py --help
Make sure you always clone and pull the latest version from Pandemic Central. Our repository can always be found at https://github.com/solveforj/pandemic-central.
Since this is still in its earliest versions, bugs and incompletions are unavoidable. Please feel free to comment or contact our developers! Your contributions are very valuable to us and this project.
Our latest version is v2.0.0. For version details, see Releases tags.
Our project can not be completed without these great sources. We do not own any data; all input data we use are open-source or permission-granted. More details about how we process this data may be found in
Here is a list of datasets we have used so far:
We also thank Plotly, TensorFlow and Python communities for very detailed and helpful documentations.
Please check out these resources for yourself!