On an interval prediction of COVID-19 ...
Document type :
Article dans une revue scientifique
Title :
On an interval prediction of COVID-19 development based on a SEIR epidemic model
Author(s) :
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Ushirobira, Rosane [Auteur]
Finite-time control and estimation for distributed systems [VALSE]

Finite-time control and estimation for distributed systems [VALSE]
Ushirobira, Rosane [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Journal title :
Annual Reviews in Control
Publisher :
Elsevier
Publication date :
2021
ISSN :
1367-5788
English keyword(s) :
COVID-19
Epidemic model
Parameter identification
Interval predictor
Epidemic model
Parameter identification
Interval predictor
HAL domain(s) :
Sciences de l'ingénieur [physics]/Automatique / Robotique
English abstract : [en]
In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model’s improvements is to reflect the ...
Show more >In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model’s improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identi- fied model is then applied to predict the SARS-CoV-2 virus propagation under various conditions of confinement. For this purpose, an interval predictor is designed, allowing variations and uncertainties in the model parameters to be taken into account. The code and the utilized data are available on Github.Show less >
Show more >In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model’s improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identi- fied model is then applied to predict the SARS-CoV-2 virus propagation under various conditions of confinement. For this purpose, an interval predictor is designed, allowing variations and uncertainties in the model parameters to be taken into account. The code and the utilized data are available on Github.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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