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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 report, a revised version of the well-known mathematical outbreak SEIR model is used to analyze the epidemic's course of COVID-19 in eight different countries. The proposed model enhancements reflect the societal feedback on pandemic and confinement features. The parameters of the SEIR model are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identified model is then applied for the prediction of the SARS-CoV-2 virus propagation under different 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 in Github.
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Submitted on : Wednesday, June 3, 2020 - 12:27:19 PM
Last modification on : Thursday, March 24, 2022 - 3:43:44 AM


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  • HAL Id : hal-02517866, version 6


Denis Efimov, Rosane Ushirobira. On an interval prediction of COVID-19 development based on a SEIR epidemic model. [Research Report] Inria. 2020. ⟨hal-02517866v6⟩



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