Prospective Analysis of Parasitic Infections in Canadian Travelers and Immigrants
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: International travel is associated with increased risk of vector-borne illnesses, particularly malaria. The objective of this study was to prospectively assess the relative frequency of parasitic diseases in Canadian travelers and to characterize demographic and travel-related predictors of these infections. METHODS: Data on Canadians and new immigrants who crossed international borders and were seen in the Tropical Disease Unit of Toronto General Hospital between November 1997 and June 2003 were prospectively collected and entered into the GeoSentinel Surveillance Network database. RESULTS: Of 3,528 returned Canadian travelers and new immigrants in the database, 1,010 had a parasitic infection diagnosed. Mean age of the 3,528 travelers was 37.3 years, and 42.6% were male. Those diagnosed with parasitic infections were more likely than the remaining cohort to have been traveling for the purpose of immigration (21.1% vs 7.1%, p < 0.001), or visiting friends and relatives (VFR) (17.9% vs 11.8%, p < 0.01). Common parasitic infections included nonhistolytica amebiasis (N= 209), malaria (N= 143), cutaneous larva migrans (N= 105), giardiasis (N= 74), and schistosomiasis (N= 48). CONCLUSIONS: Parasitic infections occurred in 29% of Canadian travelers. New immigrants and VFRs are at increased risk for malaria, as well as protozoal and helminthic infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.000 | 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 it