Maximizing tuberculosis services through private provider engagement – A case study from Pakistan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pakistan is the fourth highest contributor to the globally estimated 3.7 million tuberculosis (TB) cases. Due to the subpar condition of public sector facilities in Pakistan, the private sector remains the preferred choice, with over 90% of people accessing it for TB care. Aligning with the World Health Organization's (WHO) patient-centered approach, the private provider engagement program led by Mercy Corps (MC) and supported by the Global Fund has been actively engaging the private sector for over a decade in strengthening Pakistan's TB services through innovative interventions. Their public-private mix (PPM) strategies like, involving General Practitioners (GPs), large private hospitals, pharmacies, specimen transportation and mobile outreach chest camps, take an integrated approach (Fig. 1) to ensure treatment adherence, completion, and contact screening in reaching the last mile. In this paper, we present MC's contributions as a case study to elaborate on the crucial role of private provider engagement in improving overall TB care, increasing TB notifications, and addressing the urgent need to identify people with undiagnosed TB.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it