Market assessment of tuberculosis diagnostics in India in 2013
Bibliographic record
Abstract
India represents a significant potential market for new tests. We assessed India's market for tuberculosis (TB) diagnostics in 2013.Test volumes and unit costs were assessed for tuberculin tests, interferon-gamma release assays, sputum smear microscopy, serology, culture, speciation testing, nucleic-acid amplification tests (i.e., in-house polymerase chain reaction, Xpert(®) MTB/RIF, line-probe assays) and drug susceptibility testing. Data from the public sector were collected from the Revised National TB Control Programme reports. Private sector data were collected through a survey of private laboratories and practitioners. Data were also collected from manufacturers.In 2013, India's public sector performed 19.2 million tests, with a market value of US$22.9 million. The private sector performed 13.6 million tests, with a market value of US$60.4 million when prices charged to the patient were applied. The overall market was US$70.8 million when unit costs from the ingredient approach were used for the 32.8 million TB tests performed in the entire country. Smear microscopy was the most common test performed, accounting for 25% of the overall market value.India's estimated market value for TB diagnostics in 2013 was US$70.8 million. These data should be of relevance to test developers, donors and implementers.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".