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Reports (Research Report) Year : 2020

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

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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Dates and versions

hal-02517866 , version 1 (24-03-2020)
hal-02517866 , version 2 (27-03-2020)
hal-02517866 , version 3 (30-03-2020)
hal-02517866 , version 4 (06-04-2020)
hal-02517866 , version 5 (27-04-2020)
hal-02517866 , version 6 (03-06-2020)

Identifiers

  • HAL Id : hal-02517866 , version 6

Cite

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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