This repository contains the codes and data used in the manuscript "Inference of epidemic networks: the effect of different data types", by Oscar Fajardo-Fontiveros, Carl J. E. Suster, and Eduardo G. Altmann, developed at The University of Sydney, Sydney, NSW, Australia. The code in this repository was created by Oscar Fajardo-Fontiveros.
This package requires Python 3.8 or higher and the following dependencies:
- numpy
- pandas
- scipy
- matplotlib
To install the package in editable mode for development:
git clone https://github.com/oscarcapote/transmission_models.git
cd transmission_models
pip install -e .This will install the package in editable mode, meaning any changes you make to the source code will be immediately available without reinstalling.
After installation, you can verify the package is working correctly:
from transmission_models import *
print("Transmission Models package installed successfully!")The Jupyter Notebook Example.ipynb contains an illustration of the usage of this library.
- data/
Contains the data used in the manuscript (49 cases of positive tests in NSW, from mid 2021). Information about the time, genetic distance, and location of each case is provided in separate files.
- src/transmission_models/
Contains the main package code organized as follows:
- classes/
Contains the code that implements the transmission model and the MCMC used to sample transmission trees.
- priors/
Contains the code that implements the genetic and location models.
- utils/
Contains additional functions used in the library.
See the Example.ipynb notebook for detailed usage examples and the documentation for complete API reference.
tree_plot.js is an interactive tree visualization library build in JavaScript and D3.js. This tool allows you to:
- Interactive visualization of transmission trees with D3.js
- Customizable node colors for sampled and unsampled hosts
- Tooltips showing host attributes on hover
- Toggle between layouts: classic tree layout and infection time-based layout
- Responsive design that adapts to window resizing
In https://www.maths.usyd.edu.au/u/oscarf/tree_layout/ you can upload your jsons to visualize your sampled networks:
This webpage have been developed using tree_layout.js
Example of a tree layout visualization generated using the interactive tree visualization tool.
For complete documentation on using the tree visualization features, see the Tree Visualization Guide in the documentation.
You can also use the online tree layout tool at: https://www.maths.usyd.edu.au/u/oscarf/tree_layout/