On an interval prediction of COVID-19 development based on a SEIR epidemic model
Identifieur interne : 000128 ( Main/Exploration ); précédent : 000127; suivant : 000129On an interval prediction of COVID-19 development based on a SEIR epidemic model
Auteurs : Denis Efimov [France] ; Rosane Ushirobira [France]Source :
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.
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Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"> <p>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.</p>
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