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This project aims at modeling the propagation of the SARS-Cov-2 using a SEIRD model and a Bayesian approach.
We use a SEIR(D) model to predict the propagation of the SARS-CoV-2 virus. The effect of the lockdown is taken into account.
Our idea was to estimate the parameters of the model using data from ECDC and a Bayesian approach. For France, we also use data from Santé publique France.
Métadonnées :
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Il n'y a pas d'autres réutilisations du même créateur.