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Table 2 Short-term forecasting performance in the context of the SARS outbreak in Singapore. The sub-epidemic model outperformed the simpler growth models in terms of all of the performance metrics in short-term forecasts. Values highlighted in italics correspond to the best performance metric at a given forecasting horizon

From: A novel sub-epidemic modeling framework for short-term forecasting epidemic waves

Model Mean absolute error (MAE) Mean squared error (MSE) Mean interval score (MIS) Percentage coverage of the 95% prediction interval
4 days ahead
 Sub-epidemic wave 3.6 28.1 40.6 76.1
 Richards 3.7 28.8 79.1 63.3
 Logistic 3.8 31.1 60.3 69.4
6 days ahead
 Sub-epidemic wave 4.0 39.5 46.9 76.3
 Richards 4.1 39.7 87.9 60.4
 Logistic 4.1 42.0 66.0 69.3
8 days ahead
 Sub-epidemic wave 4.4 55.7 54.1 75.6
 Richards 4.4 54.5 94.7 59.4
 Logistic 4.4 56.9 71.1 68.9
10 days ahead
 Sub-epidemic wave 4.9 83.5 60.3 74.0
 Richards 4.8 79.3 99.0 58.9
 Logistic 4.8 81.7 77.2 68.0