https://github.com/fabriziomusacchio/sir_model
This repository contains the code for the blog post on The SIR model: A mathematical approach to epidemic dynamics. For further details, please refer to this post.
https://github.com/fabriziomusacchio/sir_model
python simulation sir-model
Last synced: about 1 month ago
JSON representation
This repository contains the code for the blog post on The SIR model: A mathematical approach to epidemic dynamics. For further details, please refer to this post.
- Host: GitHub
- URL: https://github.com/fabriziomusacchio/sir_model
- Owner: FabrizioMusacchio
- Created: 2023-07-13T00:25:08.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2023-07-13T01:10:33.000Z (almost 3 years ago)
- Last Synced: 2025-10-24T03:39:19.004Z (8 months ago)
- Topics: python, simulation, sir-model
- Language: Python
- Homepage: https://www.fabriziomusacchio.com/blog/2020-12-11-sir_model/
- Size: 366 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# The SIR Model
This repository contains the code for the blog posts on [The SIR model: A mathematical approach to epidemic dynamics](https://www.fabriziomusacchio.com/blog/2020-12-11-sir_model/) and [Interactive COVID-19 data exploration with Jupyter notebooks](https://www.fabriziomusacchio.com/blog/2020-12-15-covid19_interactive_plot/). For further details, please refer to these posts.
For reproducibility:
```powershell
conda create -n sir_model_covid19 -y python=3.9
conda activate sir_model_covid19
conda install -y mamba
mamba install -y pandas matplotlib numpy scipy scikit-learn ipykernel notebook ipympl mplcursors
```
## Acknowledgement
I acknowledge that the main code is based on this [blog post](https://numbersandshapes.net/posts/fitting_sir_to_data_in_python/) and this [documentation page](https://scientific-python.readthedocs.io/en/latest/notebooks_rst/3_Ordinary_Differential_Equations/02_Examples/Epidemic_model_SIR.html). I have made some modifications to the code to make it more readable and understandable.