Latitudinal Patterns of Travel Among Returned Travelers With Influenza: Results From the GeoSentinel Surveillance Network, 1997–2007
Bibliographic record
Abstract
BACKGROUND: Influenza is a common vaccine-preventable disease among international travelers, but few data exist to guide use of reciprocal hemisphere or out-of-season vaccines. METHODS: We analyzed records of ill-returned travelers in the GeoSentinel Surveillance Network to determine latitudinal travel patterns in those who acquired influenza abroad. RESULTS: Among 37,542 ill-returned travelers analyzed, 59 were diagnosed with influenza A and 11 with influenza B. Half of travelers from temperate regions to the tropics departed outside influenza season. Twelve travelers crossed hemispheres from one temperate region to another, five during influenza season. Ten of 12 travelers (83%) with influenza who crossed hemispheres were managed as inpatients. Proportionate morbidity estimates for influenza A acquisition were highest for travel to the East-Southeast Asian influenza circulation network with 6.13 (95% CI 4.5-8.2) cases per 1000 ill-returned travelers, a sevenfold increased proportionate morbidity compared to travel outside the network. CONCLUSIONS: Alternate hemisphere and out-of-season influenza vaccine availability may benefit a small proportion of travelers. Proportionate morbidity estimates by region of travel can inform pre-travel consultation and emphasize the ease of acquisition of infections such as influenza during travel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".