Impact of Rising Global Temperatures on Dengue Infection and Serotype Distribution: A Mini Review
Bibliographic record
Abstract
Background: Dengue virus (DENV) infection is currently one of the most significant vector-borne viral diseases in terms of global morbidity and mortality. Climate change studies have demonstrated the association between dengue virus transmission and variations in ambient temperature. We performed a mini review to evaluate whether there are differences in the association between the increase in ambient temperature and the incidence of dengue among the different dengue serotypes. Methods: For this systematic review we searched MEDLINE and PubMed databases for studies published within the last 15 years, from database inception to the exception of this review, focusing on the association between dengue incidence of serotypes and temperature variations globally. We excluded studies that involved reviews, modeling with only prospective data, prediction, or predictive models. The quality of the evidence was assessed using the Newcastle-Ottawa Scale (NOS). Findings: There is a significant association between temperature and DENV infection due to global warming. No specific dengue serotypes were identified as predominant in the reviewed studies. Aedes aegypti and Aedes Albopictus, the primary dengue vectors of DENV, have different behaviors in response to temperature changes. Discussion: The findings of this review emphasize the strong relationship between temperature and dengue incidence. Expanding the geographical scope and including more prospective studies would enhance the understanding and generalizability of these findings. Conclusion: This review showed a significant relationship between temperature increases (in the context of global warming) and dengue infection, leading to potential outbreaks. A more thorough analysis of serotypes is recommended for future studies.
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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 | 0.012 | 0.105 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".