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Record W2886570077 · doi:10.1186/s12916-018-1112-9

Epidemiological and genomic determinants of tuberculosis outbreaks in First Nations communities in Canada

2018· article· en· W2886570077 on OpenAlexafffundabout
Alexander Doroshenko, Caitlin S. Pepperell, Courtney Heffernan, Mary Lou Egedahl, Tatum D. Mortimer, Tracy M. Smith, Hailey E. Bussan, Gregory J. Tyrrell, Richard Long

Bibliographic record

VenueBMC Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsProvincial Laboratory of Public HealthAlberta Health ServicesUniversity of Alberta
FundersNational Institute of General Medical SciencesNational Institute of Allergy and Infectious DiseasesAlberta Health ServicesNational Science FoundationNational Institutes of HealthUniversity of Alberta
KeywordsOutbreakTuberculosisMedicineEpidemiologyContext (archaeology)Transmission (telecommunications)Public healthMolecular epidemiologyEnvironmental healthDemographyVirologyBiologyGenotypeGeneticsPathology

Abstract

fetched live from OpenAlex

In Canada, tuberculosis disproportionately affects foreign-born and First Nations populations. Within First Nations’ peoples, a high proportion of cases occur in association with outbreaks. Tuberculosis transmission in the context of outbreaks is thought to result from the convergence of several factors including characteristics of the cases, contacts, the environment, and the pathogen. We examined the epidemiological and genomic determinants of two well-characterized tuberculosis outbreaks attributed to two super-spreaders among First Nations in the province of Alberta. These outbreaks were associated with two distinct DNA fingerprints (restriction fragment-length polymorphisms or RFLPs 0.0142 and 0.0728). We compared outbreak isolates with endemic isolates not spatio-temporarily linked to outbreak cases. We extracted epidemiological variables pertaining to tuberculosis cases and contacts from individual public health records and the provincial tuberculosis registry. We conducted group analyses using parametric and non-parametric statistical tests. We carried out whole-genome sequencing and bioinformatic analysis using validated protocols. We observed differences between outbreak and endemic groups in the mean number of total and child-aged contacts and the number of contacts with new positive and converted tuberculin skin tests in all group comparisons (p < 0.05). Differences were also detected in the proportion of cases with cavitation on a chest radiograph and the mean number of close contacts in selected group comparisons (p < 0.02). A phylogenetic network analysis of whole-genome sequencing data indicated that most outbreak and endemic strains were closely related to the source case for the 0.0142 fingerprint. For the 0.0728 fingerprint, the source case haplotype was circulating among endemic cases prior to the outbreak. Genetic and temporal distances were not correlated for either RFLP 0.0142 (r2 = − 0.05) or RFLP 0.0728 (r2 = 0.09) when all isolates were analyzed. We found no evidence that endemic strains acquired mutations resulting in their emergence in outbreak form. We conclude that the propagation of these outbreaks was likely driven by the combination of characteristics of the source cases, contacts, and the environment. The role of whole-genome sequencing in understanding mycobacterial evolution and in assisting public health authorities in conducting contact investigations and managing outbreaks is important and expected to grow in the future.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.007
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 score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.347
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations13
Published2018
Admission routes3
Has abstractyes

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