Travel‐Associated Illness in Older Adults (>60 y)
Bibliographic record
Abstract
BACKGROUND: Older individuals represent a substantial proportion of international travelers. Because of physiological changes and the increased probability of underlying medical conditions, older travelers might be at higher risk for at least some travel-associated diseases. METHODS: With the aim of describing the epidemiology of travel-associated diseases in older adults, medical data were prospectively collected on ill international travelers presenting to GeoSentinel sites from 1997 to 2009. Seven thousand thirty-four patients aged 60 years and over were identified as older travelers and were compared to 56,042 patients aged 18-45 years, who were used as the young adult reference population. RESULTS: The proportionate morbidity of several etiological diagnoses was higher in older ill travelers compared to younger ill, including notably lower respiratory tract infections, high-altitude pulmonary edema, phlebitis and pulmonary embolism, arthropod bites, severe malaria, rickettsiosis, gastritis, peptic ulcers, esophagitis and gastroesophageal reflux disease, trauma and injuries, urinary tract infections, heart disease, and death. In contrast, acute diarrhea, upper respiratory tract infections, flu and flu-like illnesses, malaria, dengue, genital infections, sexually transmitted diseases, and schistosomiasis proportionate morbidities were lower among the older group. CONCLUSION: Older ill travelers are more likely to suffer from certain life-threatening diseases and would benefit from reinforcement of specific preventive measures including use of anti-thrombosis compression stockings and sufficient hydration and exercises during long-distance flights, hand hygiene, use of disposable handkerchiefs, consideration of face-masks in crowded conditions, influenza and pneumococcal vaccines, progressive acclimatization to altitude, consideration of acetazolamide, and use of repellents and mosquito nets. Antibiotics for the presumptive treatment of respiratory and urinary tract infections may be considered, as well as antacid medications. At-risk patients should be referred to a specialist for medical evaluation before departing, and optimal control of co-morbidities such as cardiovascular and chronic obstructive pulmonary diseases should be achieved, particularly for high-altitude travel.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".