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Record W2985244392 · doi:10.1186/s12889-019-7868-9

A systematic review of BCG vaccination policies among high-risk groups in low TB-burden countries: implications for vaccination strategy in Canadian indigenous communities

2019· review· en· W2985244392 on OpenAlexafffundabout
Lena Faust, Yoko Schreiber, Natalie Bocking

Bibliographic record

VenueBMC Public Health · 2019
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of ManitobaMcGill UniversityNOSM UniversityMcGill University Health Centre
FundersIndigenous Services Canada
KeywordsMedicineBiostatisticsVaccinationEnvironmental healthPublic healthIndigenousEpidemiologyVaccination policyTuberculosisBCG vaccineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Bacille Calmette-Guérin (BCG) vaccination against tuberculosis (TB) is widespread in high-TB-burden countries, however, BCG vaccination policies in low-burden countries vary. Considering the uncertainties surrounding BCG efficacy and the lower likelihood of TB exposure in low-incidence countries, most have discontinued mass vaccination, choosing instead a targeted vaccination strategy among high-risk groups. Given the increased risk of TB infection in Canadian Indigenous communities compared to the general Canadian population, these communities are a pertinent example of high-incidence groups in an otherwise low-burden country, warranting particular consideration regarding BCG vaccination strategy. This systematic review aims to synthesise and critically appraise the literature on BCG vaccination strategies in high-risk groups in low-incidence settings to provide policy considerations relevant to the Canadian Indigenous context. METHODS: A literature search of the Medline and Embase databases was conducted, returning studies pertaining to BCG vaccine efficacy, TB incidence under specific vaccination policies, BCG-associated adverse events, and vaccination policy guidelines in low-burden countries. Study screening was tracked using the Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia), and data pertaining to the above points of interest were extracted. RESULTS: The final review included 49 studies, spanning 15 countries. Although almost all of these countries had implemented a form of mass or routine vaccination previously, 11 have since moved to targeted vaccination of selected risk groups, in most cases due to the low risk of infection among the general population and thus the high number of vaccinations needed to prevent one case in the context of low-incidence settings. Regarding identifying risk groups for targeted screening, community-based (rather than individual risk-factor-based) vaccination has been found to be beneficial in high-incidence communities within low-incidence countries, suggesting this approach may be beneficial in the Canadian Indigenous setting. CONCLUSIONS: Community-based vaccination of high-incidence communities may be beneficial in the Canadian Indigenous context, however, where BCG vaccination is implemented, delivery strategies and potential barriers to achieving adequate coverage in this setting should be considered. Where an existing vaccination program is discontinued, it is crucial that an effective TB surveillance system is in place, and that case-finding, screening, and diagnostic efforts are strengthened in order to ensure adequate TB control. This is particularly relevant in Canadian Indigenous and other remote or under-served communities, where barriers to surveillance, screening, and diagnosis persist.

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 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)0.021
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.727
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0160.025
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.098
GPT teacher head0.421
Teacher spread0.323 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations24
Published2019
Admission routes3
Has abstractyes

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