Summary statistics for forecasting outbreak months across 2018 to 2021.

DIR (Dengue Incidence Rate) observations (n = 180) were classified one month ahead of time as being predicted true outbreaks with DIR exceeding 50 (or 150) per 100,000 if the posterior probability of DIR exceeding 50 (or 150) was greater than a cut-off probability of 0⋅21 (or 0⋅13). True Positive measures the hit rate, or equivalently the proportion of true outbreaks correctly detected, whilst False Positive measures the proportion of non-outbreaks incorrectly classified as outbreaks. Accuracy represents the proportion of observations whose outbreak classification matched the true observed state (such as a predicted outbreak coinciding with an outbreak). Precision measures the proportion of predicted outbreaks which were true outbreaks. Finally, the AUC is the area under the Receiver Operating Characteristic (ROC) curve, is used as a measure of our model’s skill for distinguishing between outbreaks. The cut-off probabilities were calibrated using historical data (prior to 2018) and thus, outbreak forecasting model performance is reflective of a realistic application of our framework by authorities. 95% CIs are the corresponding 95% confidence intervals [57, 58]. Further analyses of outbreak classification performance were performed (see Table D in S1 Appendix).