Journal article
An updated ensemble forecasting model for district-level dengue prediction in the Mekong Delta Region of Vietnam: model refinement and evaluation
Wellcome open research, Vol.11, pp.1-12
21/08/2026
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Abstract
Background: The original district-level dengue forecasting ensemble for Vietnam’s Mekong Delta Region (MDR) showed strong overall accuracy but had two key limitations: forecasted outbreak peaks lagged behind observed timing, and outbreaks were under-detected during periods of rapidly increasing incidence.
Methods: We evaluated 57 candidate models varying in spatial structure, seasonal representation, and covariates, including flexible harmonic seasonality and climate-driven covariates (mosquito thermal suitability, cumulative precipitation), assessed using the Continuous Ranked Probability Score and Brier score. The six best-performing models were combined into a revised ensemble using district- and horizon-specific Brier score weighting, trained on 2010–2015 data, cross-validated over 2016–2020, and evaluated over 2021–2025 for the on-season period (April–November), using the 95th percentile of historical district-month cases as the epidemic threshold.
Results: At the 3-month forecast horizon, the revised ensemble achieved 66.3% sensitivity and 89.1% specificity, compared with 43.4% sensitivity and 91.7% specificity for the original model, and overall accuracy improved from 84% to 87% (see Extended Data). The revised model also reduced the temporal lag in outbreak predictions observed previously.
Conclusions: The revised ensemble improves outbreak detection sensitivity while maintaining high specificity and reduces forecast lag, supporting more timely and targeted dengue prevention and control interventions in the MDR.
Details
- Title
- An updated ensemble forecasting model for district-level dengue prediction in the Mekong Delta Region of Vietnam: model refinement and evaluation
- Creators
- Wala Draidi Areed - The University of QueenslandVinh Bui - Southern Cross UniversityDaniel M. Weinberger - Yale University School of Public Health (USA)Dung Phung - The University of Queensland
- Publication Details
- Wellcome open research, Vol.11, pp.1-12
- Publisher
- Wellcome
- Grant note
- This study was funded by the Wellcome Trust [226474/Z/22/Z] as part of the E-Dengue project.
- Identifiers
- 991013396901802368
- Copyright
- © 2026 Draidi Areed W et al.
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article