Health status of newly arrived refugees in Toronto, Ont: Part 1: infectious diseases.
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of selected infectious diseases among newly arrived refugee patients and whether there is variation by key demographic factors. DESIGN: Retrospective chart review. SETTING: Primary care clinic for refugee patients in Toronto, Ont. PARTICIPANTS: A total of 1063 refugee patients rostered at the clinic from December 2011 to June 2014. MAIN OUTCOME MEASURES: Demographic information (age, sex, and region of birth); prevalence of HIV, hepatitis B, hepatitis C, Strongyloides, Schistosoma, intestinal parasites, gonorrhea, chlamydia, and syphilis infections; and varicella immune status. RESULTS: The median age of patients was 29 years and 56% were female. Refugees were born in 87 different countries. Approximately 33% of patients were from Africa, 28% were from Europe, 14% were from the Eastern Mediterranean Region, 14% were from Asia, and 8% were from the Americas (excluding 4% born in Canada or the United States). The overall rate of HIV infection was 2%. The prevalence of hepatitis B infection was 4%, with a higher rate among refugees from Asia (12%, P < .001). Hepatitis B immunity was 39%, with higher rates among Asian refugees (64%, P < .001) and children younger than 5 years (68%, P < .001). The rate of hepatitis C infection was less than 1%. Strongyloides infection was found in 3% of tested patients, with higher rates among refugees from Africa (6%, P = .003). Schistosoma infection was identified in 15% of patients from Africa. Intestinal parasites were identified in 16% of patients who submitted stool samples. Approximately 8% of patients were varicella nonimmune, with higher rates in patients from the Americas (21%, P < .001). CONCLUSION: This study highlights the importance of screening for infectious diseases among refugee patients to provide timely preventive and curative care. Our data also point to possible policy and clinical implications, such as targeted screening approaches and improved access to vaccinations and therapeutics.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".