Anti-Trypanosoma cruzi antibodies in Latin American migrants in transit through the México- USA border
Bibliographic record
Abstract
INTRODUCTION: In recent years, American trypanosomiasis has become an emergent public health problem in countries receiving migrant populations such as México, USA, Canada or those in Europe. OBJECTIVE: To analyze the prevalence of anti-Trypanosoma cruzi antibodies in Latin American migrants on their way to USA and Canada by means of serological techniques. MATERIAL AND METHODS: ELISA and IHA were performed to detect anti-T. cruzi antibodies. Also, each participant filled out a socioeconomic questionnaire to determine the associated factors with seropositive cases, which could facilitate the transmission in the migrants' country of origin. RESULTS: Total seroprevalence among the studied population was 20% (24/120). The highest prevalence was found in migrants from Guatemala with 37.5% (6/16), followed by Honduras (22.6%; 12/53), El Salvador (16%; 4/25), and México (8.7%, 3/23). From the total 120 surveyed migrants, 105 (87.5%) recognized the vector of Chagas' disease, and 62 (59%) assured having been bitten by it. Highly significant statistical associations were found between infection and the construction materials for walls and the presence of pets (dogs) inside houses (p≤0.01), as well as with the building materials for backyards, inadequate basic services, and animal breeding inside corrals built around dwellings (p≤0.05). CONCLUSION: Non-endemic countries receiving migrants from endemic areas should enhance or develop better health policies to prevent transfusion-transmitted Chagas or congenital parasite transmission.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".