Global dengue epidemic worsens with record 14 million cases and 9000 deaths reported in 2024
Bibliographic record
Abstract
December 2024. We then performed a generalised linear regression model to understand country-level determinants of dengue-related mortality. In 2024, 14.1 million dengue cases were reported globally, surpassing the historic milestone of 7 million observed in 2023. This figure represents a twofold increase compared to 2023 and a 12-fold rise compared to 2014 (n=1,206,644). In 2024, 9,508 dengue-related deaths were recorded, resulting in a global case-fatality rate of 0.07%. In the regression analysis, countries in the Southern hemisphere (incidence rate ratio [IRR]: 5.95, 95% CI: 4.19-8.46), aged population (IRR 1.04, CI: 1.01-1.07), and mean annual temperature (IRR 1.21, CI: 1.16-1.26) were significantly associated with higher dengue-related mortality per million population. The ongoing dengue outbreak underscores the urgent need for global investment in DENV research, vaccine development, vector control, and therapeutic strategies. We urge the inclusion of DENV in the WHO's Research and Development Priority Disease list to address this growing global health threat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".