Infectious Disease Acquisition in Pediatric International Travelers: A 10-Year Review at a Canadian Tertiary Care Hospital
Bibliographic record
Abstract
Introduction: Children are frequent international travelers and may acquire serious infectious diseases during travel. We undertook a retrospective 10-year review examining children admitted to hospital with infectious diseases associated with international travel at a Canadian tertiary care pediatric hospital. Methods: Retrospective chart review was performed on select travel-related infectious diseases in children ranging in age from birth to <18 years who were admitted at the Hospital for Sick Children in Toronto between January 1st, 2009 and December 31st, 2018. Cases were identified using ICD-10 discharge codes. Patient demographics, travel history, epidemiological data, disease, and prophylaxis history were documented. Results: A total of 154 children were hospitalized with a travel-related infection over a 10-year period. The most common diagnoses were typhoid or paratyphoid fever (n = 58, 38%), malaria (n = 57, 37%), and hepatitis A (n = 14, 8%). The median age of those infected was 8 years (IQR 3-12). There were 120 (78%) children who were Canadian born, 31 (20%) immigrants and 3 (2%) who were visiting Canada. Of those who lived in Canada, 112 (90%) travelled for the purpose of visiting friends and relatives (VFR), 6 (5%) for tourism and 2 (2%) for humanitarian work. India was typically known for the acquisition of infection for typhoid or paratyphoid fever, and Nigeria for malaria. Hepatitis A was most commonly acquired in Pakistan. Conclusion: Imported infectious diseases continue to be a significant issue in travelers returning from trips suggesting improved preventative pre-travel care. VFR children are a group that should, in particular, be targeted for appropriate pre-travel advice and care.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".