Table 1.
Model parameters of the SEIR model (adapted from Zhao et al. [30]).
Fig 1.
Configuration of the hybrid model.
The hybrid model combines a mechanistic model (SEIR) with a machine learning model (Neural Network).
Table 2.
List of covariates.
Fig 2.
Temporal cross-validation scheme.
Δt was set to 3 and 7 days for the predictions at 3 and 7 days ahead, respectively.
Fig 3.
Model predictions of intensive care bed occupancy at the national-level.
a) Predictions 3-days ahead of intensive occupancy at the national-level for the three models (shaded areas represent 95% confident intervals); b) corresponding Mean Absolute Error (MAE) calculated on test data.
Fig 4.
Model predictions of intensive care bed occupancy at the hospital-level.
Prediction at the hospital-level for a medium-sized hospital (a) and the largest hospital (b) in the canton of Zurich.
Fig 5.
Covariance importance for each phase.
An asterisk represents a negative deviation.