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 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.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Biology - 10(2020), 1 vom: 31. Dez.

Sprache:

Englisch

Beteiligte Personen:

Bakhta, Athmane [VerfasserIn]
Boiveau, Thomas [VerfasserIn]
Maday, Yvon [VerfasserIn]
Mula, Olga [VerfasserIn]

Links:

Volltext

Themen:

COVID-19
Epidemiology
Forecasting
Journal Article
Model reduction
Reduced basis

Anmerkungen:

Date Revised 18.02.2021

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/biology10010022

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM319604233