- Describes the SIRC (susceptible-infectious-recovered-carrier) epidemiological model.
- Integrates the model equations in python code.
- Describes the system's parameters and their influences by solving the system of ordinary differential equations for different initial conditions and different parameter values.
This repository contains essential scripts for running SIRC model simulations as well as supplementary scripts to run SIR model simulations:
- sirsirc.yml: a conda environment provided to setup and install the required libraries to run python simulations for SIR and SIRC models.
- sirc.py: provides a python implementation of the SIRC model's ODEs.
- sirc.R (1): provides an R implementation of the SIRC model's ODEs.
- sir.py (2): provides a python implementation of the SIR model's ODEs.
To setup the conda environment with dependancies, download the sirsirc.yml file and run the following:
conda env create -f sirsirc.yml
- (1) https://rstudio-pubs-static.s3.amazonaws.com/111132_79dd08ebb42e4e2d927c4a88729b72bd.html
- (2) https://scipython.com/book/chapter-8-scipy/additional-examples/the-sir-epidemic-model/
- Jinde Cao, Yi Wang, Abdulaziz Alofi, Abdullah Al-Mazrooei, Ahmed Elaiw, Global stability of an epidemic model with carrier state in heterogeneous networks, IMA Journal of Applied Mathematics, Volume 80, Issue 4, August 2015, Pages 1025–1048.
- Modelling Epidemics, Lecture 5: Deterministic compartmental epidemiological models in homogeneous populations, Andrea Doeschl-Wilson
- Lectures on Mathematical Modelling of Biological Systems, G. Bastin, 2018