Programmatic Implementation of Contact Investigation in Eight African Countries
Bibliographic record
Abstract
The objective was to implement CI under national tuberculosis programmatic conditions and to advocate for its scaling up. Contact investigation was implemented in 150 Basic Management Units identified across eight countries. The target populations (children <5 years and persons living with HIV (PLHIV)) were evaluated during home and clinic visits using standardized tools, clinical examinations and, according to each country, additional tests. Contacts with active TB received TB treatment and those eligible received TB preventive therapy (TPT). Data were collected each quarter using standardized forms. Meetings were organized with partners to share preliminary results and advocate for scaling up. From October 2020 to December 2021, 9049 home visits were performed. The proportions of children <5 years and PLHIV who were screened and diagnosed with active TB were, respectively, 2.6% and 10.1%. Ninety-three percent of children <5 years and 98% of PLHIV living at home received TPT or TB treatment, respectively. The scale-up for contact investigation partially or at national level in 2022 was effective in six of the eight countries included in the project. These results indicate that CI is feasible under programmatic conditions within the National TB Programs of African countries.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".