Rabies post-exposure prophylaxis started during or after travel: A GeoSentinel analysis
Bibliographic record
Abstract
BACKGROUND: Recent studies demonstrate that rabies post-exposure prophylaxis (RPEP) in international travelers is suboptimal, with only 5-20% of travelers receiving rabies immune globulin (RIG) in the country of exposure when indicated. We hypothesized that travelers may not be receiving RIG appropriately, and practices may vary between countries. We aim to describe the characteristics of travelers who received RIG and/or RPEP during travel. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center review of international travelers exposed to potentially rabid animals, collecting information on RPEP administration. Travelers who started RPEP before (Group A) and at (Group B) presentation to a GeoSentinel clinic during September 2014-July 2017 were included. We included 920 travelers who started RPEP. About two-thirds of Group A travelers with an indication for rabies immunoglobulin (RIG) did not receive it. Travelers exposed in Indonesia were less likely to receive RIG in the country of exposure (relative risk: 0.30; 95% confidence interval: 0.12-0.73; P = 0.01). Travelers exposed in Thailand [Relative risk (RR) 1.38, 95% Confidence Interval (95% CI): 1.0-1.8; P = 0.02], Sri Lanka (RR 3.99, 95% CI: 3.99-11.9; P = 0.013), and the Philippines (RR 19.95, 95% CI: 2.5-157.2; P = 0.01), were more likely to receive RIG in the country of exposure. CONCLUSIONS/SIGNIFICANCE: This analysis highlights gaps in early delivery of RIG to travelers and identifies specific countries where travelers may be more or less likely to receive RIG. More detailed country-level information helps inform risk education of international travelers regarding appropriate rabies prevention.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".