Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
Résumé
We propose a forecasting method for predicting epidemiological health series on a two-week horizon at regional and interregional resolution. The approach is based on the model orderreduction of parametric compartmental models and is designed to accommodate small amounts ofsanitary data. The efficiency of the method is shown in the case of the prediction of the number ofinfected people and people removed from the collected data, either due to death or recovery, duringthe two pandemic waves of COVID-19 in France, which took place approximately between Februaryand November 2020. Numerical results illustrate the promising potential of the approach
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