Compound and cascading effects of climatic extremes on dengue outbreak risk in the Caribbean: An impact-based modelling framework with long-lag and short-lag interactions

This study highlights the potential value of incorporating interaction terms in prediction models to account for the compound and cascading effects of climate on disease risk, which could enhance model explainability and predictive performance. aimed to cocreate an impact-based modelling framework that employs interactions between climatic predictors to forecast the probability of a climate-sensitive infectious disease outbreak 3 months in advance.

The authors found that a three-way interaction between the 3-month averaged mean temperature anomaly lagged by 3 months, 6-month SPI (SPI-6) lagged by 5 months, and SPI-6 lagged by 1 month best predicted dengue outbreak risk in Barbados. The impact-based modelling framework with long-lag and short-lag interactions explicitly accounted for the compound and cascading effects of drought, heat, and excessively wet conditions on dengue outbreak risk in Barbados.