SrasV1, 2020, Analysis, bibRecord, 000006

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

Identifieur interne : 000006 ( 2020/Analysis ); précédent : 000005; suivant : 000007

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

Auteurs : Denis Efimov [France] ; Rosane Ushirobira [France]

Source :

RBID : Hal:hal-02517866

Abstract

In this brief report, a modified version of the well-known mathematical epidemic model SEIR is used to analyze the epidemics course of COVID-19 in six different countries. To this goal, the parameters of the SEIR model are identified by using publicly available data for the corresponding countries: France, Italy, Spain, Germany, Brazil and Russia. 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 data are available in Github.

Url:

https://hal.inria.fr/hal-02517866

Affiliations:

France

Links toward previous steps (curation, corpus...)

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to stream Hal, to step Curation: 000113
to stream Hal, to step Checkpoint: 000009
to stream Main, to step Merge: 000006
to stream Main, to step Curation: 000006
to stream Main, to step Exploration: 000006
to stream 2020, to step Extraction: 000006

Links to Exploration step

Hal:hal-02517866

Le document en format XML

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<front><div type="abstract" xml:lang="en">              <p>In this brief report, a modified version of the well-known mathematical epidemic model SEIR is used to analyze the epidemics course of COVID-19 in six different countries. To this goal, the parameters of the SEIR model are identified by using publicly available data for the corresponding countries: France, Italy, Spain, Germany, Brazil and Russia. 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 data are available in Github.</p>
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   |wiki=    Sante
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   |étape=   Analysis
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   |clé=     Hal:hal-02517866
   |texte=   On an interval prediction of COVID-19 development based on a SEIR epidemic model
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On an interval prediction of COVID-19 development based on a SEIR epidemic model

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

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