Chagas and Vector-Borne Disease Exposures in an Indigenous Community in the Ecuadorian Amazon: A Retrospective Study
Bibliographic record
Abstract
There are limited data on vector-borne diseases from the Ecuadorian Amazon, particularly among marginalized Indigenous populations. From a survey of Shuar communities in Ecuador, we measured IgG antibodies to Trypanosoma cruzi, dengue virus, and Leishmania spp. The prevalence of IgG antibodies was 7.4% for T. cruzi, 21.3% for dengue, and 96.8% for Leishmania spp. There was an increase in the risk of dengue infections with increasing age (per year; adjusted odds ratio [adj. OR]: 1.03, 95% CI: 1.01-1.05, P = 0.001) and among females (adj. OR: 2.17, 95% CI: 1.03-4.57, P = 0.041). There was an increase in T. cruzi anti-Tc24 IgG antibody levels with greater age (Spearman r = 0.553, P = 0.05). This study showed a high prevalence or exposure to Chagas disease, dengue, and Leishmania spp. There remains an unmet need for surveillance to monitor the transmission of Chagas and other vector-borne diseases and their associated morbidity in marginalized communities in the Ecuadorian Amazon.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".