The 2012 dengue outbreak in Madeira: exploring the origins
Bibliographic record
Abstract
In 2012, Madeira reported its first major outbreak of dengue. To identify the origin of the imported dengue virus, we investigated the interconnectivity via air travel between dengue-endemic countries and Madeira, and compared available sequences against GenBank. There were 22,948 air travellers to Madeira in 2012, originating from twenty-nine dengue-endemic countries; 89.6% of these international travellers originated from Venezuela and Brazil. We developed an importation index that takes into account both travel volume and the extent of dengue incidence in the country of origin. Venezuela and Brazil had by far the highest importation indices compared with all other dengue-endemic countries. The importation index for Venezuela was twice as high as that for Brazil. When taking into account seasonality in the months preceding the onset of the Madeira outbreak, this index was even seven times higher for Venezuela than for Brazil during this time. Dengue sequencing shows that the virus responsible for the Madeira outbreak was most closely related to viruses circulating in Venezuela, Brazil and Columbia. Applying the importation index, Venezuela was identified as the most likely origin of importation of dengue virus via travellers to Madeira. We propose that the importation index is a new additional tool that can help to identify and anticipate the most probable country of origin for importation of dengue into currently non-endemic countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".