- published
- 2021-05-16
- reference
- Anne-Flore Baron, Olivier Boulant, Ivan Panico, and Nicolas Vayatis, A Compartmental Epidemiological Model Applied to the Covid-19 Epidemic, Image Processing On Line, 11 (2021), pp. 105–119. https://doi.org/10.5201/ipol.2021.323
Communicated by Gregory Randall
Demo edited by Anne-Flore Baron
Abstract
The objective of this work is to provide a sophisticated but accessible compartmental epidemic model. Our algorithm is highly inspired from the compartmental model developed by Sofonea and al. in 2020. This model has been used as a reference for several working groups in France during the Covid-19 crisis. Each individual is allocated to a compartment according to her age, her current state with respect to the disease, as well as the length of time she has been in that state. The model then reproduces the mechanisms of transition from one state to another: mathematically, this translates into a system of recurrence relations. It captures how much individuals interact with one another through a parameter that estimates compliance with hygiene measures and lifestyle habits. The present work aims to make the model implementation fully transparent as well as the corresponding code available and give control to users so that they are able to test the model in total transparency. Focus has been put on reproducibility and explanation of the various parameters. The hard-coded parameters correspond to the data for the Covid-19 epidemic in France.
Download
- full text manuscript: PDF (1.1MB)
- source code: TAR/GZ
History
- Note from the editor: the source code was updated on September 7, 2021 to set the latest versions of matplotlib and numpy in the requirements.txt file. The original version of the code is available from here.
- Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.