Using information theory to optimise epidemic models for real-time prediction and estimation

doi:10.1371/journal.pcbi.1007990

Using information theory to optimise epidemic models for real-time prediction and estimation

Fig 8

Empirical prediction accuracy.

We compare the APE metric (dotted blue, left y axis) to the percentage of true incidence values, I_s+1, which fall outside the 95% prediction intervals of (dotted red, right y axis) across the window search space k. The dashed line gives k* (black) and k = 7 (grey). The top graph presents results for the influenza 1918 dataset, while the bottom one is for SARS 2003 data. We find that heuristic weekly windows lead to appreciably larger forecasting error than the APE selections.

doi: https://doi.org/10.1371/journal.pcbi.1007990.g008