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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Online Access: | https://www.mdpi.com/2079-7737/10/1/22 |
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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 |
work_keys_str_mv |
AT athmanebakhta epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic AT thomasboiveau epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic AT yvonmaday epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic AT olgamula epidemiologicalforecastingwithmodelreductionofcompartmentalmodelsapplicationtothecovid19pandemic |
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1724364484881940480 |