This Python program predicts the transmission of tuberculosis by clustering reported infected cases by their geographic location. The program uses the k-means or hierarchical algorithm for clustering.
To install the necessary packages, first clone the repository:
git clone https://github.com/digmouse233/tuberculosis-transmission-predictor.git
cd tuberculosis-transmission-predictor
Then, create a virtual environment and activate it:
python -m venv venv
source venv/bin/activate # for Linux/Mac OS
venv\Scripts\activate.bat # for Windows
Finally, install the required packages with pip:
pip install -r requirements.txt
This will install all the necessary dependencies for the project.
To run the program, use the main.py script.
python main.pyRunning this script will generate two .csv files with time-sequence data within the sir folder for each location specified in the data directory. These files record the state of the SIR model over time.
A visualization of the model's progression can be accessed locally by running the Dash application, available at http://127.0.0.1:8050 in your web browser after the script execution.
This program is released under the MIT license. See the LICENSE file for more.