Business travel-associated illness: a GeoSentinel analysis†
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Analysis of a large cohort of business travelers will help clinicians focus on frequent and serious illnesses. We aimed to describe travel-related health problems in business travelers. Methods: GeoSentinel Surveillance Network consists of 64 travel and tropical medicine clinics in 29 countries; descriptive analysis was performed on ill business travelers, defined as persons traveling for work, evaluated after international travel 1 January 1997 through 31 December 2014. Results: Among 12 203 business travelers seen 1997-2014 (14 045 eligible diagnoses), the majority (97%) were adults aged 20-64 years; most (74%) reported from Western Europe or North America; two-thirds were male. Most (86%) were outpatients. Fewer than half (45%) reported a pre-travel healthcare encounter. Frequent regions of exposure were sub-Saharan Africa (37%), Southeast Asia (15%) and South Central Asia (14%). The most frequent diagnoses were malaria (9%), acute unspecified diarrhea (8%), viral syndrome (6%), acute bacterial diarrhea (5%) and chronic diarrhea (4%). Species was reported for 973 (90%) of 1079 patients with malaria, predominantly Plasmodium falciparum acquired in sub-Saharan Africa. Of 584 (54%) with malaria chemoprophylaxis information, 92% took none or incomplete courses. Thirteen deaths were reported, over half of which were due to malaria; others succumbed to pneumonia, typhoid fever, rabies, melioidosis and pyogenic abscess. Conclusions: Diarrheal illness was a major cause of morbidity. Malaria contributed substantial morbidity and mortality, particularly among business travelers to sub-Saharan Africa. Underuse or non-use of chemoprophylaxis contributed to malaria cases. Deaths in business travelers could be reduced by improving adherence to malaria chemoprophylaxis and targeted vaccination for vaccine-preventable diseases. Pre-travel advice is indicated for business travelers and is currently under-utilized and needs improvement.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it