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Table 2 ARGO performance compared to alternative methods for the validation period of February 28, 2015 to July 2, 2016

From: Using electronic health records and Internet search information for accurate influenza forecasting

  real-time forecast 1 week forecast 2 week forecast 3 week
RMSE
 ARGO 0.341 0.540 0.604 0.704
 healthmap 0.530 0.590 0.932 0.949
 ar4 0.902 0.909 0.838 0.780
 naive 1 (0.206) 1 (0.330) 1 (0.439) 1 (0.552)
MAE
 ARGO 0.386 0.502 0.529 0.563
 healthmap 0.527 0.564 0.697 0.700
 ar4 0.994 0.952 0.852 0.766
 naive 1 (0.146) 1 (0.248) 1 (0.341) 1 (0.435)
RMSPE
 ARGO 0.425 0.472 0.524 0.593
 healthmap 0.622 0.613 0.868 0.871
 ar4 0.959 1.006 0.958 0.920
 naive 1 (0.108) 1 (0.173) 1 (0.232) 1 (0.293)
MAPE
 ARGO 0.448 0.466 0.489 0.494
 healthmap 0.592 0.593 0.666 0.654
 ar4 1.034 1.018 0.935 0.860
 naive 1 (0.083) 1 (0.139) 1 (0.194) 1 (0.250)
Correlation
 ARGO 0.995 0.963 0.916 0.823
 healthmap 0.987 0.956 0.843 0.774
 ar4 0.961 0.896 0.842 0.776
 naive 0.963 0.900 0.829 0.745
Error reduction of ARGO over the best alternative (in %)
 RMSE 35.63 8.38 27.94 9.77
 MAE 26.75 11.07 24.16 19.49
 RMSPE 31.63 22.94 39.59 31.93
 MAPE 24.29 21.42 26.58 24.42
  1. The evaluation metrics are defined in Table 1. The benchmark methods are the same as Table 1 except that the ensemble method of Santillana et al. [11] is replaced by a refined version broadcasted by the Healthmap Flu Trends system. Boldface highlights the best method for each metric in each forecasting time horizon. RMSE, MAE, RMSPE, MAPE are relative to the error of the naive method, i.e., the numbers are the ratio of the error of a given method over that of the naive method; the absolute error of the naive method is given in the round bracket. Table S4 in the Additional file 1 gives absolute error of all methods. For each forecasting time horizon and each evaluation metrics, the error reduction of ARGO over the best alternative method is given in the second half of the table.