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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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
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spelling doaj-de5c586dddb742c996b28c7d1a1622fa2021-01-01T00:05:41ZengMDPI AGBiology2079-77372021-12-0110222210.3390/biology10010022Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 PandemicAthmane Bakhta0Thomas Boiveau1Yvon Maday2Olga Mula3Université Paris-Saclay, CEA, Service de Thermo-Hydraulique et de Mécanique des Fluides, 91191 Gif-sur-Yvette, FranceSorbonne Université, Institut Carnot Smiles, 75005 Paris, FranceSorbonne Université and Université de Paris, CNRS, Laboratoire Jacques-Louis Lions (LJLL), F-75005 Paris, FranceCEREMADE, CNRS, UMR 7534, Université Paris-Dauphine, PSL University, 75016 Paris, FranceWe 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.https://www.mdpi.com/2079-7737/10/1/22COVID-19epidemiologyforecastingmodel reductionreduced basis
collection DOAJ
language English
format Article
sources DOAJ
author Athmane Bakhta
Thomas Boiveau
Yvon Maday
Olga Mula
spellingShingle Athmane Bakhta
Thomas Boiveau
Yvon Maday
Olga Mula
Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
Biology
COVID-19
epidemiology
forecasting
model reduction
reduced basis
author_facet Athmane Bakhta
Thomas Boiveau
Yvon Maday
Olga Mula
author_sort Athmane Bakhta
title Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
title_short Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
title_full Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
title_fullStr Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
title_full_unstemmed Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
title_sort epidemiological forecasting with model reduction of compartmental models. application to the covid-19 pandemic
publisher MDPI AG
series Biology
issn 2079-7737
publishDate 2021-12-01
description 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.
topic COVID-19
epidemiology
forecasting
model reduction
reduced basis
url https://www.mdpi.com/2079-7737/10/1/22
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AT thomasboiveau epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic
AT yvonmaday epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic
AT olgamula epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic
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