Travel-acquired infections and illnesses in Canadians: surveillance report from CanTravNet surveillance data, 2009-2011.
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: Important knowledge gaps exist in our understanding of migration medicine practice and the impact of pathogens imported by Canadian travellers. We present here a comprehensive, Canada-specific surveillance summary of illness in a cohort of returned Canadian travellers and new immigrants. METHODS: We extracted and analyzed (using standard parametric and nonparametric techniques) data from the Canadian Travel Medicine Network (CanTravNet) database for ill returned Canadian travellers and new immigrants who presented to a Canadian GeoSentinel Surveillance Network site between September 2009 and September 2011. RESULTS: During the study period, 4365 travellers and immigrants presented to a CanTravNet site, 3943 (90.3%) of whom were assigned a travel-related diagnosis. Among the 3115 non-immigrant travellers with a definitive travel-related diagnosis, arthropod bite (n = 127 [4.1%]), giardiasis (n = 91 [2.9%]), malaria (n = 77 [2.5%]), latent tuberculosis (n = 73 [2.3%]), and strongyloidiasis (n = 66 [2.1%]) were the most common specific etiologic diagnoses. Among the 828 immigrants with definitive travel-related diagnoses, the most frequent etiologies were latent tuberculosis (n = 229 [27.7%]), chronic hepatitis B (n = 182 [22.0%]), active tuberculosis (n = 97 [11.7%]), chronic hepatitis C (n = 89 [10.7%]), and strongyloidiasis (n = 41 [5.0%]). Potentially serious infections, such as dengue fever (61 cases) and enteric fever due to Salmonella enterica serotype Typhi or Paratyphi (36 cases), were common. Individuals travelling for the purpose of visiting friends and relatives (n = 500 [11.6% of those with known reason for travel]) were over-represented among those diagnosed with malaria and enteric fever, compared with other illnesses (for malaria 34/94 [36.2%] v. 466/4221 [11.0%]; for enteric fever, 17/36 [47.2%] v. 483/4279 [11.3%]) (both p < 0.001). For cases of malaria, there was also overrepresentation (compared with other illnesses) from business travellers (22/94 [23.4%] v. 337/4221 [8.0%]) and males (62/94 [66.0%] v. 1964/4269 [46.0%]) (both p < 0.001). Malaria was more likely than other illnesses to be acquired in sub-Saharan Africa (p < 0.001), whereas dengue was more likely than other illnesses to be imported from the Caribbean and South East Asia (both p = 0.003) and enteric fever from South Central Asia (24/36 [66.7%]) (p < 0.001). INTERPRETATION: This analysis of surveillance data on ill returned Canadian travellers has detailed the spectrum of imported illness within this cohort. It provides an epidemiologic framework for Canadian practitioners encountering ill returned travellers. We have confirmed that travel to visit friends and relatives confers particularly high risks, which underscores the need to improve pretravel intervention for a population that is unlikely to seek specific pretravel advice. Potentially serious and fatal illnesses such as malaria and enteric fever were common, as were illnesses of public health importance, such as tuberculosis and hepatitis B.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it