PandemieGrippaleV1, 2020, Analysis, bibRecord, 000128

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

Identifieur interne : 000128 ( 2020/Analysis ); précédent : 000127; suivant : 000129

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 report, a modified version of the well-known mathematical outbreak SEIR model is used to analyze the epidemics course of COVID-19 in six 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 and Russia. The identified model is then applied for the prediction of the SARS-CoV-2 virus propagation under 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...)

to stream Hal, to step Corpus: 000432
to stream Hal, to step Curation: 000432
to stream Hal, to step Checkpoint: 000128
to stream Main, to step Merge: 000128
to stream Main, to step Curation: 000128
to stream Main, to step Exploration: 000128
to stream 2020, to step Extraction: 000128

Links to Exploration step

Hal:hal-02517866

Le document en format XML

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   |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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