EpidemicKabu 0.1.5

New methodology to identify waves, peaks, and valleys from epidemic curve

EpidemicKabu a new method to identify epidemic waves and their peaks and valleys

Kabu is a new methodology to identify waves, peaks, and valleys from epidemic curve. The algorithm in explain in doi:.. as well as some examples.

Description of files in this repository:

1. epidemickabu/ contains the modules of the package:

   • kabu.py is the main module. It makes the necessary calculations for the subsequent identification of waves, and peaks and valleys. The main input is a dataset with two variables (i.e., cases, and dates) and the kernels to smooth both the epidemic curve and its first derivative with a Gaussian filter.

   • kabuWaves.py is a module to estimate the waves. You could set an optional threshold to filter the days delimiting the waves. There are some examples in examples/ that give you and idea of the magnitude of this value. You can also filter the waves changing the kernel's value.

   • kabuPeaksValleys.py is a module to estimate the Peaks and Valleys of each identified wave.

2. examples/ contains the files to replicate examples of how to use the library. The examples are made with COVID-19 data for 15 countries:

   • data/ is the input data used in all the research.
   • dataframes/ is created to save the output dataframes.
   • plots/ is created to save the output plots.
   • exampleUseLibrary.ipynb shows basic examples to use the library.
   • exploringLibrary/.ipynb explores attributes and methods from the classes in the library.
   • The other files show the steps for some analysis made with the results obtained with the library for COVID-19 data.

3. test/ contains the files to test the code.

4. additional/ contains some notebooks showing the step by step of the algorithm.

Installation

NOTE: This project was made in Python 3.10.6

1. Install the library using pip

   pip install epidemickabu
   

2. Import the library

   import epidemickabu as ek
   

Contributing

This project is in progress and it requires some improvments. Therefore, if you have any suggestion that would make this better, please fork the repository and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/improvments)
3. Commit your Changes (git commit -m 'Adding some improvment)
4. Push to the Branch (git push origin feature/improvments)
5. Open a Pull Request

Contact

• Lina M Ruiz G - [e-mail]

Acknowledgments

• Anderson Alexis Ruales Barbosa
• Oscar Ignacio Mendoza Cardozo