Epidemic Modeling

🧬 Tweak transmission rate, recovery rate, death rate, number of people, and many more! 🧬

⚙️ Graphical User Interface with sliders and buttons. ⚙️

👁️ Visual and graphical interpretation of results from the simulation 👁️

🔬 Randomized simulation 🔬

🧫 Inspired by SEIDR Model 🧫

Features

• Every parameters of the simulation is editable through an interactive GUI 🖥
• Humans are travelling randomly but logically and are represented by dots 👦
• Humans can wear a mask and mask are 80% effective 🧢
• Humans wearing a mask are represented by a "+" and do not easily infect as well as being harder to infect ⛑️
• The simulation is almost fully randomized but keeps logic with given values 🎲
• You can adjust the speed of the simulation with the slider 🏃
• You can tweak some specific parameters of the simulation 🧰
• At the end of the simulation, you can see the evolution of the population through time 📊
• ... and many more! 🎯

Demo

One wave of the epidemic was simulated

3hm49ZR.mp4

Three waves of the epidemic were simulated

HHOF2NKU9f.mp4

Masked dots example

7yZKhat.mp4

Support 👨‍💻

Any problems with running the script and any questions please create a new issue here.

You can also contribute to this project by requesting new features here.

I never ask for money for my open source projects. However, you can still tip me if you want. I am a Brave Verified Creator!

Prerequisites

• Python 3.7.0+

Get a copy of the Project. Assuming you have git installed, open your Terminal and enter:

git clone 'https://github.com/marcpinet/epidemic-modeling.git'

To install all needed requirements run the following command in the project directory:

pip install -r requirements.txt

Running 🏃

After that you can proceed to start the program by running main.py.

Authors

• Marc Pinet - Initial work - marcpinet

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

• Hat tip to anyone whose code was used.

Contributions

Special thanks to loicpantano for some ideas and marcusaasjensen for its participation in the project (he made a its own simulation in C# of an airport with graphs, see marcus' simulation).

We were in the same team for this project and we worked together on different programs.