Child Contact Case Management—A Major Policy-Practice Gap in High-Burden Countries
Bibliographic record
Abstract
The 2021 Global Tuberculosis (TB) report shows slow progress towards closing the pediatric TB detection gap and improving the TB preventive treatment (TPT) coverage among child and adolescent contacts. This review presents the current knowledge around contact case management (CCM) in low-resource settings, with a focus on child contacts, which represents a key priority population for CCM and TPT. Compelling evidence demonstrates that CCM interventions are a key gateway for both TB case finding and identification of those in need of TPT, and their yield and effectiveness should provide a strong rationale for prioritization by national TB programs. A growing body of evidence is now showing that innovative models of care focused on community-based and patient-centered approaches to household contact investigation can help narrow down the CCM implementation gaps that we are currently facing. The availability of shorter and child-friendly TPT regimens for child contacts provide an additional important opportunity to improve TPT acceptability and adherence. Prioritization of TB CCM implementation and adequate resource mobilization by ministries of health, donors and implementing agencies is needed to timely close the gap.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".