We propose a forecasting method for predicting epidemiological health series on a two-week horizon at the regional and interregional level . The approach is based on model order reduction of parametric compartmental models, and is designed to accommodate small amount of sanitary data. The efficiency of the method is examined in the case of the prediction of the number of hospitalized  infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020. Numerical results illustrate the promising potential of the approach.
We propose a forecasting method for predicting epidemiological health series on a two-week horizon at the regional and interregional resolution . The approach is based on model order reduction of parametric compartmental models, and is designed to accommodate small amount of sanitary data. The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020. Numerical results illustrate the promising potential of the approach.
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