Welcome to card_deck’s documentation!

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.

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

Installation

The library package has been published on PyPi, so can be found here: https://pypi.org/project/tiered-antibiotic-resistance-model/, and can be installed as follows:

pip install tiered-antibiotic-resistance-model

Requirements

There are no additional required libraries

Contents

• Project Description
  • Objective
  • Source Code
  • Download
• Warwick iGEM computational modelling
  • Table of contents
  • Summary of project
  • Custom modelling
• Example Usage
  • Importing the module
  • Running the model
  • Changing parameters and settings in-line
• Interface
  • The run function
  • The run_and_output function
  • Infection object
  • Treatment object
  • Person object
  • Model object
  • DataHandler object
  • DataRenderer object
  • Params object
  • Settings object

Indices and tables

• Index

• Module Index

• Search Page