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SEIR model with scenario analysis and model-based predictive control to simulate the effect policies

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BIOMATH COVID19-Model

Original code by Ryan S. McGee. Modified by T.W. Alleman in consultation with the BIOMATH research unit headed by prof. Ingmar Nopens.

Copyright (c) 2020 by T.W. Alleman, BIOMATH, Ghent University.

Introduction

Our code implements a SEIRS infectious disease dynamics model with extensions to model the effect of quarantining detected cases. Our code allows to perform Monte Carlo simulations, calibrate model parameters and calculate optimal government policies using a model predictive controller (MPC). A white paper and source code of our previous work can be found on the BIOMATH website.

Check the documentation website for more information about the code and the models.

Demo

A demo of the model can be found here. This notebook can also be run in the browser through binder.

Binder

Installation

The information needed to install the required packages, can be found here on the documentation website.

Acknowledgements

  • The repository setup is a derived version of the data science cookiecutter providing a consistent structure.
  • Original code by Ryan S. McGee

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