Variations in annual dengue intensities are explained by temperature anomalies

Area of Science:

• Epidemiology
• Public Health
• Climate Science

Background:

• Global dengue incidence has significantly increased over recent decades.
• Rising dengue cases and enhanced surveillance complicate the identification of unusually intense transmission years.
• Existing methods struggle to standardize dengue intensity across diverse geographical and temporal contexts.

Purpose of the Study:

• To develop a standardized measure for dengue intensity, the Relative Intensity Score (RISc).
• To analyze long-term dengue incidence trends and identify peak intensity years globally.
• To investigate factors associated with elevated dengue intensity, particularly temperature anomalies.

Main Methods:

• A hierarchical Bayesian Poisson regression model was employed to analyze annual dengue incidence data from 57 countries (1990-2023).
• A novel Relative Intensity Score (RISc) was calculated by comparing reported cases against a modeled long-term trend.
• A July-June annual timeframe was used for Southern Hemisphere countries to accurately capture transmission seasons.

Main Results:

• The study identified 1995, 1998, 2019, and 2023 as the years with the highest global RISc.
• High dengue intensity (RISc) demonstrated a tendency to occur in multi-year cycles.
• Temperature anomalies were found to be the strongest correlate of elevated RISc.

Conclusions:

• The Relative Intensity Score (RISc) offers the first standardized global metric for comparing dengue intensity across time and locations.
• Understanding dengue intensity patterns and drivers is crucial for predicting future outbreaks.
• Climate change, particularly temperature anomalies, plays a significant role in modulating dengue transmission intensity.