Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic

We propose a forecasting method for predicting epidemiological health series on a two-week horizon at regional and interregional resolution. The approach is based on the model order reduction of parametric compartmental models and is designed to accommodate small amounts of sanitary data. The effici...

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Bibliographic Details
Main Authors: Athmane Bakhta, Thomas Boiveau, Yvon Maday, Olga Mula
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Biology
Subjects:
Online Access:https://www.mdpi.com/2079-7737/10/1/22
Description
Summary:We propose a forecasting method for predicting epidemiological health series on a two-week horizon at regional and interregional resolution. The approach is based on the model order reduction of parametric compartmental models and is designed to accommodate small amounts of sanitary data. The efficiency of the method is shown in the case of the prediction of the number of infected people and people removed from the collected data, either due to death or recovery, during the two pandemic waves of COVID-19 in France, which took place approximately between February and November 2020. Numerical results illustrate the promising potential of the approach.
ISSN:2079-7737