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Record W2913110994 · doi:10.14745/ccdr.v45i23a04

Tuberculosis in Canada: 2017

2019· article· en· W2913110994 on OpenAlex
Marie LaFreniere, Hamidah Hussain, Ning He, M McGuire

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanada Communicable Disease Report · 2019
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of TorontoPublic Health Agency of Canada
FundersBritish Columbia Centre for Disease ControlDepartment of Health, Western Cape GovernmentNova Scotia Department of Health and WellnessMinistry of Health, SaskatchewanPublic Health AgencyPublic Health Agency of CanadaAlberta Health Services
KeywordsTuberculosisPublic healthMedicineEpidemiologyPopulationDemographyIncidence (geometry)Context (archaeology)IndigenousEnvironmental healthGeographyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Tuberculosis (TB) is a major global health problem that affected an estimated 10 million people worldwide in 2017. The Public Health Agency of Canada monitors active TB disease through a national surveillance system, which is a collaborative effort with the provinces and territories. OBJECTIVE: To present an epidemiological summary of active TB cases reported in 2017. Results are discussed in the context of the previous year's data. Treatment outcomes for cases diagnosed in 2016 are also presented. METHODS: The Canadian Tuberculosis Reporting System is a case-based surveillance system that maintains non-nominal data on people diagnosed with active TB disease in Canada. Data are collected annually from the provinces and territories, analyzed by the Public Health Agency of Canada and validated by each province and territory. RESULTS: There were 1,796 cases of active TB reported in Canada in 2017 compared with 1,750 cases in 2016, representing a 2.6% increase. There was a corresponding increase in the incidence rate from 4.8 to 4.9 per 100,000 population. Foreign born individuals continued to make up the majority of cases (71.8%) and the incidence rate remained highest among Canadian born Indigenous people (21.5 per 100,000 population), in particular, among the Inuit population (205.8 per 100,000 population). Consistent with the previous decade, TB incidence rates in 2017 continued to be higher among males (5.5 per 100,000) compared with females (4.3 per 100,000), and the majority of cases (45.6%) were between the ages of 15 and 44 years. The incidence rate was highest among adults over 75 years of age (13.8 cases per 100,000 for males and 7.2 for females). Of the TB cases diagnosed in 2016 where outcomes were reported, 80.4% were treated successfully. CONCLUSION: Although the incidence rate of TB in Canada in 2017 remained low in the global context and has been relatively stable over the last decade, both the case count and rate have been gradually increasing since 2014. Indigenous and foreign born Canadians continued to be disproportionately represented among TB cases. Canadian TB surveillance data are an important source of information for monitoring progress and informing public health action related to reducing the burden of TB in Canada, with the ultimate goal of TB elimination.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.285
Teacher spread0.264 · 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