In this project, we study the following:
- How sequential mutant strains of a virus, each mutnt more transmissible than its parent, compete in population
- How the heterogeneity in human contact patterns affect the competition dynamics and infection spread
| Team member name |
|---|
| Sudarshan Anand |
| Rohini Janivara |
| Alejandro Danies Lopez |
We recommend using a Linux/Unix(Mac) environment. For windows users, we recommend using WSL2 to create a linux environment.
- Install
ryeusing the following command:
curl -sSf https://rye.astral.sh/get | bash
source "$HOME/.rye/env"cdinto the project directory and run the following command to create a virtual environment:
rye init .- Add dependencies as follows:
rye add jupyter networkx numpy matplotlib seaborn scipy tqdm sympy pyvis plotly - Activate the virtual environment using the following command:
source .venv/bin/activate- Move into
Network_generation - Run the
network_gen.pyto generate the synthetic networks
cd Network_generation
python network_gen.py- The folder
Real_world_datacontains all the data we have tried on for the calibration - We finally calibrated on Influenza data (
Real_world_data/calibration/Fludata_US_2016_2024.csv) and on the US High school contact network (Real_world_data/high_school_nw.txt) - The calibration is done in
calibration.ipynb
-
The
simulations_and_analysisfolder has all the notebooks and script files used for the simulation of the infection spread on various contact networks (synthetic and real-world), and the analysis part done for obtaining metrics for epidemic analysis and parameter sensitivity -
At the end of running the simulations, the results are stored in a
results_finalfolder