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Record W7043911273

Tuberculosis infection prevalence among foreign-born Canadian residents: A modelling study

2023· dissertation· en· W7043911273 on OpenAlexfundaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2023
Typedissertation
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchFaculty of Medicine and Health, University of SydneyMcGill University
KeywordsTuberculosisEpidemiologyDiseasePrevalenceIncidence (geometry)Population
DOInot available

Abstract

fetched live from OpenAlex

Background: Tuberculosis (TB) disproportionately impacts foreign-born persons living in Canada.Typically, they have acquired TB infection (TBI) in their country of origin and progress to TB disease during the months and years after landing.An understanding of TBI prevalence among foreign-born persons is necessary to further develop targeted TB prevention strategies, but prevalence is currently unknown.TBI prevalence was estimated among foreign-born Canadian permanent residents and citizens (foreign-born Canadians).Methods: Annual risk of infection trends were generated using a previously developed Gaussian process regression model.These trends were used to estimate the probability of TB infection among people immigrating to Canada by age, year of birth, and year of immigration.These probabilities were combined with Canadian census data to estimate TBI prevalence and 95% uncertainty intervals (95%UI) among foreign-born Canadians originating from 168 countries in census years 2001, 2006, 2011, and 2016.TBI prevalence estimates were also stratified by age, TB disease incidence in country of origin, province/territory of residence, and prevalence of infection acquired within the two preceding years for the 2016 census year.Results: Estimated TBI prevalence among foreign-born Canadians did not significantly change over time and was 25% (95%UI: 20-35%), 24% (20-33%), 23% (19-30%), and 22% (19-28%) for census years 2001, 2006, 2011, and 2016, respectively.In 2016, estimated prevalence increased with age at immigration from 8% (6-16%) among persons 0-14 years of age to 65% (50-74%) among persons ≥75 years.Prevalence also increased with TB disease incidence in the country of origin from 9% (5-22%) among those from countries with incidence of 0-9 cases per 100,000 persons to 35% (22-46%) among those from countries with incidence ≥200 cases per 100,000 persons.Estimated prevalence was lowest in Quebec, 19% (16-25%), and highest in Alberta and British Columbia, 24% (21-29%) and 24% (20-30%), respectively.Lastly, only an estimated 0.05% (0.04-0.07%) of foreign-born Canadians in 2016 had been infected in the previous two years.Conclusions: Approximately one-quarter of foreign-born Canadians have TBI, a proportion that has remained relatively stable over time, and is similar to that estimated for foreign-born residents of other high-income countries.Despite this high estimated prevalence, only a small

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.037
GPT teacher head0.310
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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