The Visiting Friends or Relatives Traveler in the 21st Century: Time for a New Definition
Bibliographic record
Abstract
BACKGROUND: Travelers visiting friends or relatives (VFR travelers) are a group identified with an increased risk of travel-related illness. Changes in global mobility, travel patterns, and inter-regional travel led to reappraisal of the classic definition of the term VFR. METHODS: The peer-reviewed literature was accessed through electronic searchable sites (PubMed/Medline, ProMED, GeoSentinel, TropNetEurop, Eurosurveillance) using standard search strategies for the literature related to visiting friends/relatives, determinants of health, and travel. We reviewed the historic and current use of the definition of VFR traveler in the context of changes in population dynamics and mobility. RESULTS: The term "VFR" is used in different ways in the literature making it difficult to assess and compare clinical and research findings. The classic definition of VFR is no longer adequate in light of an increasingly dynamic and mobile world population. CONCLUSIONS: We propose broadening the definition of VFR travelers to include those whose primary purpose of travel is to visit friends or relatives and for whom there is a gradient of epidemiologic risk between home and destination, regardless of race, ethnicity, or administrative/legal status (eg, immigrant). The evolution and application of this proposed definition and an approach to risk assessment for VFR travelers are discussed.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.013 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".