# A Tri-Model Prediction Approach for COVID-19 ICU Bed Occupancy: A Case Study
## 4 Results & Evaluation
For 1-week ahead predictions, from 23 November 2020 until 22 March 2021, the actual day and 3-day MA of all Models' Average for MAPE were 6.26% and 4.79%, for RMSE were 20.44 ICIUs and 17.54 ICIUs, for \(R^{2}\) were 98% and 99%, and for MAE were 17.73 ICIUs and 15.09 ICIUs, respectively. Regarding the 2-weeks ahead prediction, from 7/12 until 22/3 the actual day and 3-day MA of all Models' Average MAPE were 12.14% and 11.07%, for RMSE were 41.28 ICIUs and 38.15 ICIUs, for \(R^{2}\) were 95% and 96%, and for MAE were 36.77 ICIUs and 33.52 ICIUs, respectively. Finally, for the 3-weeks ahead prediction, from 21/12 until 22/3 the actual day and 3-day MA of all Models' Average MAPE were 18.55% and 17.81%, for RMSE were 69.3 ICIUs and 66.22 ICIUs, for \(R^{2}\) were 90% and 91%, and for MAE were 61.59 ICIUs and 58.29 ICIUs, respectively. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Geographical Area** & \begin{tabular}{c} **Weeks** \\ **Ahead** \\ **Prediction** \\ **Target** \\ \end{tabular} & \begin{tabular}{c} **ARTXP and** \\ **ARIMA** \\ **ARIMA** \\ **(Actual/3d)** \\ **(\%)** \\ \end{tabular} & \begin{tabular}{c} **ARIMA and** \\ **SARIMAX** \\ **(Actual/3d)** \\ **(\%)** \\ \end{tabular} & \
\begin{tabular}{c} **Multivariate** \\ **Regression** \\ **(Actual/3d)** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **All Models’** \\ **Average** \\ **(Actual/3d)** \\ **(\%)** \\ \end{tabular} \\ \hline Thessaloniki & 1 & 12.22/11.36 & 13.35/12.41 & 13.09/11.88 & 11.53/10.69 \\  & 2 & 26.46/25.12 & 27.86/25.74 & 22.63/20.77 & 21.80/19.53 \\  & 3 & 41.97/39.89 & 32.72/31.82 & 35.95/34.17 & 29.80/27.95 \\ \hline Northern & 1 & 17.26/15.92 & 9.36/7.99 & 9.74/8.12 & 10.88/9.12 \\  & 2 & 32.05/29.52 & 21.80/19.40 & 18.80/16.50 & 20.61/17.98 \\  & 3 & 52.56/49.56 & 34.44/33.77 & 30.05/29.18 & 31.94/30.94 \\ \hline Greece & 1 & 8.15/7.51 & 5.05/4.69 & 5.53/4.80 & 5.45/4.73 \\  & 2 & 16.73/15.48 & 13.90/13.11 & 9.73/8.52 & 11.40/10.24 \\  & 3 & 24.15/23.28 & 23.49/22.87 & 21.32/19.80 & 18.81/17.86 \\ \hline Attica & 1 & 7.07/6.47 & 5.83/4.60 & 7.92/6.26 & 6.26/4.79 \\  & 2 & 14.76/13.79 & 12.20/10.87 & 14.07/12.74 & 12.14/11.07 \\  & 3 & 23.96/23.50 & 17.63/16.69 & 21.42/20.19 & 18.55/17.81 \\ \hline
**Overall** & & & & & \\
**Average** & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: MAPE of Predicted vs. Actual ICIUs. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Geographical Area** & \begin{tabular}{c} **Weeks** \\ **Ahead** \\ **Prediction** \\ **Target** \\ \end{tabular} & \begin{tabular}{c} **ARTXP and** \\ **ARIMA** \\ **(Actual/3d)** \\ **(ICUs)** \\ \end{tabular} & \begin{tabular}{c} **ARIMA and** \\ **SARIMAX** \\ **(Actual/3d)** \\ **(\%)** \\ \end{tabular} & \
\begin{tabular}{c} **Multivariate** \\ **Regression** \\ **(Actual/3d)** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **All Models’** \\ **Average** \\ **(Actual/3d)** \\ **(ICUs)** \\ \end{tabular} \\ \hline Thessaloniki & 1 & 16.88/16.00 & 16.81/15.25 & 15.98/14.17 & 16.56/15.14 \\  & 2 & 35.58/33.38 & 33.13/30.13 & 25.03/22.33 & 31.25/28.61 \\  & 3 & 49.57/46.88 & 34.97/33.03 & 36.28/33.86 & 40.27/37.92 \\ \hline Northern & 1 & 41.96/39.20 & 20.54/16.86 & 76.28/74.66 & 46.26/43.57 \\  & 2 & 70.25/65.88 & 48.01/43.60 & 39.26/35.50 & 52.51/48.33 \\  & 3 & 107.01/102.87 & 66.60/64.29 & 59.29/56.03 & 77.63/74.40 \\ \hline Greece & 1 & 54.47/52.32 & 32.71/28.12 & 34.14/28.91 & 40.44/36.45 \\  & 2 & 100.46/94.69 & 73.40/69.97 & 61.64/55.47 & 78.50/73.38 \\  & 3 & 139.97/134.86 & 124.58/122.09 & 113.60/107.02 & 126.05/121.32 \\ \hline Attica & 1 & 19.87/19.32 & 18.17/15.21 & 23.29/18.08 & 20.44/17.54 \\  & 2 & 46.40/45.08 & 35.21/32.10 & 42.24/37.27 & 41.28/38.15 \\  & 3 & 83.28/82.27 & 55.60/52.41 & 69.02/63.98 & 69.30/66.22 \\ \hline
**Overall** & & & & & \\
**Average** & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: RMSE of Predicted vs. Actual ICIUs. In addition, in Tables 2-5 we highlighted with bold text the best individual value per prediction horizon, model and geographical area.