Recommendations for the screening of paediatric latent tuberculosis infection in indigenous communities: a systematic review of screening strategies among high-risk groups in low-incidence countries
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) continues to be a global public health concern. Due to the presence of multiple risk factors such as poor housing conditions and food insecurity in Canadian Indigenous communities, this population is at particularly high risk of TB infection. Given the challenges of screening for latent TB infection (LTBI) in remote communities, a synthesis of the existing literature regarding current screening strategies among high-risk groups in low-incidence countries is warranted, in order to provide an evidence base for the optimization of paediatric LTBI screening practices in the Canadian Indigenous context. METHODS: A literature search of the Embase and Medline databases was conducted, and studies pertaining the evaluation of screening strategies or screening tools for LTBI in paediatric high-risk groups in low-incidence countries were included. Studies focusing on LTBI screening in Indigenous communities were also included, regardless of whether they focused on a paediatric population. Their results were summarized and discussed in the context of their relevance to screening strategies suitable to the Canadian Indigenous setting. Grey literature sources such as government reports or policy briefs were also consulted. RESULTS: The initial literature search returned 327 studies, with 266 being excluded after abstract screening, and 36 studies being included in the final review (original research studies: n = 25, review papers or policy recommendations: n = 11). In the examined studies, case identification and cost-effectiveness of universal screening were low in low-incidence countries. Therefore, studies generally recommended targeted screening of high-risk groups in low-incidence countries, however, there remains a lack of consensus regarding cut-offs for the incidence-based screening of high-risk communities, as well as regarding the utility and prioritization of individual risk-factor-based screening of high-risk groups. The utility of the TST compared to IGRAs for LTBI detection in the pediatric population also remains contested. CONCLUSIONS: Relevant strategies for targeted screening in the Canadian Indigenous context include community-level incidence-based screening (screening based on geographic location within high-incidence communities), as well as individual risk-factor-based screening, taking into account pertinent risk factors in Indigenous settings, such as poor housing conditions, malnutrition, contact with an active case, or the presence of relevant co-morbidities, such as renal disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.131 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".