The Ockham’s razor applied to COVID-19 model fitting French data

Mirko Fiacchini (1) , Mazen Alamir (1)

1 GIPSA-MODUS - GIPSA - Modelling and Optimal Decision for Uncertain Systems

This paper presents a data-based simple model for fitting the available data of the Covid-19 pandemic evolution in France. The time series concerning the 13 regions of mainland France have been considered for fitting and validating the model. An extremely simple, two-dimensional model with only two parameters demonstrated to be able to reproduce the time series concerning the number of daily demises caused by Covid-19, the hospitalizations, intensive care and emergency accesses, the daily number of positive test and other indicators, for the different French regions. These results might contribute to stimulate a debate on the suitability of much more complex models for reproducing and forecasting the pandemic evolution since, although relevant from a mechanistic point of view, they could lead to nonidentifiability issues.

Mots clés: Covid-19 pandemic; parametric identification; data-based approaches

Domaines: Automatique / Robotique; Systèmes dynamiques [math.DS]

Mirko Fiacchini, Mazen Alamir. The Ockham’s razor applied to COVID-19 model fitting French data. 2020. ⟨hal-03014669v1⟩