207. Travel Related Risk Behaviors and Antibiotic Use among Older Travelers
Bibliographic record
Abstract
Abstract Background Older travelers (≥ 60 years) are a unique risk population for travel related infections and adverse events from antibiotics. We evaluated the differences in travel characteristics, exposures, illnesses and antibiotic use among older travelers and those between 18 – 59 y using a prospective, observational cohort of US Department of Defense (DoD) beneficiaries traveling outside the US for ≤ 6.5 months (TravMil). Methods Adult DoD beneficiaries were enrolled pre-travel. Itineraries limited to Western/Northern Europe, Canada, or New Zealand and active duty personnel on military travel were excluded. Demographics, itineraries and prescriptions were abstracted. A post-travel survey collected information on exposures and illnesses (travelers’ diarrhea (TD), influenza-like illness (ILI) or febrile illness). Categorical variables were analyzed using chi-square or Fishers exact test and the Mann-U Whitney test was used for continuous variables. Results Of the 1468 travelers, 755 were ≥ 60y and 719 were < 60y. Asia (35%) and South/Central America (28%) were the most common travel regions. Older travelers were more likely to be Caucasian (80% vs. 67%), male (52% vs. 39%) and travel for tourism (84% vs. 51%) (p< 0.05). Younger travelers were more likely engage in risk behaviors (e.g. consume poorly cooked meat or seafood (16% vs 9%) or street vendor food (26% vs 8.6%), wade in fresh water (24% vs. 18%), and non-compliance with malaria prophylaxis (22% vs 12%) (p< 0.05). Older travelers had a lower incidence of TD (18% vs 24%), and a higher proportion of cases with loose stool or mild TD that did not interfere with daily activities (63% vs. 51%) (p< 0.05). Inappropriate antibiotic use for loose stool or mild TD were similar among the two age groups (67% vs 59%). Non-significant trends of lower incidence and mild infections were observed for ILI and febrile illness in older travelers. Conclusion Older travelers were less likely to engage in risk behaviors, had a lower TD incidence and reported mild diarrheal symptoms. Inappropriate antibiotic use for loose stool or mild TD was common in both age groups. Enhancing antibiotic stewardship is important for older travelers to prevent potential side effects, drug interactions and antibiotic resistance. Disclosures All Authors: No reported disclosures
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".