Tuberculosis control in Sudan against seemingly insurmountable odds.
Bibliographic record
Abstract
SETTING: Sudan, Africa's largest and one of its poorest countries, in which civil disturbance, resource limitation and communications difficulties are substantial impediments to delivery of health services. OBJECTIVES: To 1) illustrate the burden of tuberculosis; 2) review measures taken to control the disease; 3) outline the introduction of the DOTS strategy; and 4) demonstrate the trend in the output of the DOTS strategy. METHODS: Published information on general health, tuberculosis and health structure provide the setting. Routine reports illustrate the trend in case notification in Sudan, and outcome of treatment by period of enrollment on treatment (cohort). RESULTS: Since 1992, sputum smear microscopy centres have been established in existing health facilities (179 of a total 290 targeted centres). By the end of the second quarter of 1998, 82,860 cases of tuberculosis had been reported, of whom 52% were sputum smear-positive cases. Of these, 89% had no history of previous treatment for as much as one month. The treatment outcomes for 11,000 new smear-positive cases were reported by the end of the second quarter of 1997; the proportion of notified cases for whom treatment results were available increased from 16% in 1994 to 63% in 1996. Of these, 72% were successfully treated, increasing from 62% in 1994 to 73% in 1996. CONCLUSIONS: Despite seemingly overwhelming odds, the DOTS strategy has been successfully commenced and is in the process of expansion throughout the country, with monitoring of the quality of diagnostic examinations and improvements in treatment outcome. Further improvement is necessary, but appears feasible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".