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Competing_pathogens_Heterogenous_networks

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Introduction

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

Contributors

Team member name
Sudarshan Anand
Rohini Janivara
Alejandro Danies Lopez

Setup

We recommend using a Linux/Unix(Mac) environment. For windows users, we recommend using WSL2 to create a linux environment.

  1. Install rye using the following command:
curl -sSf https://rye.astral.sh/get | bash
source "$HOME/.rye/env"
  1. cd into the project directory and run the following command to create a virtual environment:
rye init .
  1. Add dependencies as follows:
rye add jupyter networkx numpy matplotlib seaborn scipy tqdm sympy pyvis plotly 
  1. Activate the virtual environment using the following command:
source .venv/bin/activate

Files

Synthetic networks generation

  • Move into Network_generation
  • Run the network_gen.py to generate the synthetic networks
cd Network_generation
python network_gen.py

Real world data calibration

  • The folder Real_world_data contains 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

Simulations

  • The simulations_and_analysis folder 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_final folder

About

In this project, we explore the impact of heterogeneity in contact network structure on the infection dynamics of two competing pathogen strains

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