Seroprevalence of human toxocariasis in Latin America and the Caribbean: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: The current study aimed to quantitatively synthesize available evidence regarding the seroprevalence of human toxocariasis in Latin America and the Caribbean. Methods: A systematic research involving six electronic databases was conducted using a research strategy that combined MeSH terms with free terms. Article selection and information extraction were performed using a double and independent approach. The Newcastle-Ottawa tool was used to assess the risk of bias in the included articles. The meta-analysis used the random-effects approach, with subgroup analysis and sensitivity analysis for risk of bias also being performed. Results: = 99%). The prevalence of the main characteristics observed in seropositive patients were as follows: ocular toxocariasis (30.0%), asymptomatic (26.0%), and presence of dogs at home (68.0%). In addition, the seroprevalence was lower in studies including only adults than in those including children or both. In contrast, no differences in seroprevalences were found between studies conducted in the community and hospital. Conclusion: The overall seroprevalence of human toxocariasis in Latin America and the Caribbean was high. Notably, our findings showed that the seroprevalence was increased among populations who kept a dog at home but was decreased in populations comprising only adults. Our findings can be used to establish epidemiological surveillance strategies for the prevention and early identification of toxocariasis.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.021 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".