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State–Space Forecasting of Schistosoma haematobium Time-Series in Niono, Mali
Figure 5
Schistosoma haematobium consultation rate time-series forecasting accuracy and dispersion for the district of Niono, Mali.
Panel A: Mean absolute percentage error (MAPE) values between Schistosoma haematobium time-series (TS) observations for the district of Niono, Mali, and their corresponding h-month horizon forecasts measure external accuracy. The average coefficient of variance (
) for h-month horizon forecast probability density functions reflect prediction dispersion. MAPE and 
values are displayed as a function of h-month horizon forecasts. MAPE and 
values for 1–5 month horizon forecasts were circa 25 and 45%, respectively. Therefore, panels A and B demonstrate that forecast accuracy and dispersion are reasonable for short horizons. Of note, MAPE, unlike 
, values assess the skill of h-month horizon forecasts. 
and PI values are rarely reported outside the econometric literature; yet, they have paramount importance for calculating, e.g., the probability that a future observation will be smaller or greater than the expected forecast distribution mean by a certain margin. Alternatively, the number of individuals at risk may be calculated for a specified probability.
doi: https://doi.org/10.1371/journal.pntd.0000276.g005
