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On an interval prediction of COVID-19 development based on a SEIR epidemic model

Denis Efimov 1 Rosane Ushirobira 1
1 VALSE - Finite-time control and estimation for distributed systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : 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.
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Submitted on : Wednesday, January 27, 2021 - 12:36:33 PM
Last modification on : Friday, January 21, 2022 - 3:10:36 AM
Long-term archiving on: : Wednesday, April 28, 2021 - 6:43:17 PM


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Denis Efimov, Rosane Ushirobira. On an interval prediction of COVID-19 development based on a SEIR epidemic model. Annual Reviews in Control, Elsevier, 2021, ⟨10.1016/j.arcontrol.2021.01.006⟩. ⟨hal-03122861⟩



Les métriques sont temporairement indisponibles