tiered-antibiotic-resistance-model 4.0.0

A validated computational model of the spread of an antibiotic resistant pathogens in a hospital, with and without our diagnostic tool for quickly identifying it

Warwick iGEM computational modelling

A repository containing code for custom computational modelling components within the 2021 Warwick team iGEM project.

We used Python to implement a discrete time, stochastic, compartmental model of the spread of antibiotic resistant pathogens through a population.

Model abstract

We propose a validated computational model of the spread of an antibiotic resistant pathogens in a hospital, with and without our diagnostic tool for quickly identifying it, and show that in a relevant scenario it reduces the presence of antibiotic resistant pathogens in our selected scenario, showing our product is beneficial in the real-world.

Writeup, documentation and production code

The writeup for the entire project can be found here:

• As a markdown document
• As a PDF file
• As part of the Warwick iGEM 2021 wiki

The documentation for the production code can be found here:

• On readthedocs.io

The final production code for the project can be found here:

• As a standalone python file
• As a package on PyPI

Team

The core team members of the project are:

• Edmund Goodman, Model design and software implementation
• Axel Schoerner Emillon, Model design and data analysis

With thanks to Reanna Gregory, Alex Darlington, and the rest of the 2021 iGEM Warwick team for their time discussing the initial design and ways to improve the model.

Contributions and errata

If you find a bug in the code or an error in the writeup, feel free to submit a pull request or an issue through GitHub, and we will endeavour to fix it!