The public health approach to antiretroviral treatment (ART) service scale-up in Ethiopia: the first two years of free ART, 2005-2007.
Bibliographic record
Abstract
BACKGROUND: The World Health Organization has proposed a public health approach to antiretroviral therapy (ART) to promote scaling up access to treatment in developing countries. Ethiopia has been implementing this approach for ART provision since 2005. OBJECTIVE: To describe the Ethiopian experience in the scale-up of ART services using the public health approach. METHODS AND PATIENTS: This is a retrospective study of patients who were started on ART since 2005. We used data from the monthly HIV Care and ART Update reports of the Ethiopian AIDS Resource Center, analyzing the trend of ART service provision and site expansion from the second quarter of 2005 to the second quarter of 2007. Data were analyzed for 1) patients enrolled for chronic HIV/AIDS care, 2) patients started on ART and 3) facilities providing ART. RESULTS: The number of ART sites increased from 3 in early 2005 to 265 in early June 2007. During that time, the number of ART patients increased from 8,276 to 92,450 and of patients receiving chronic HIV/AIDS care from 13,773 to 156,729. The proportion of females and children on ART and of patients residing outside of Addis Ababa also sharply increased. CONCLUSION: The sharp increase in the number of sites providing ART service and patients started on ART is mainly due to the simplification and standardization of ART delivery models and employing nurses for ART provision. The public health approach is an innovative strategy to scale up ART service provision to poor and rural communities where it hasn't been possible to provide the service based on the traditional delivery model.
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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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".