Impact of decentralisation of antiretroviral therapy services on HIV testing and care at a population level in Agago District in rural Northern Uganda: results from the Lablite population surveys
Bibliographic record
Abstract
Background: We conducted unlinked cross-sectional population-based surveys in Northern Uganda before and after antiretroviral therapy (ART) provision (including Option B+ [lifelong ART for pregnant/breast-feeding women]) at a local primary care facility (Lira Kato Health Centre [HC]). Prior to decentralisation, people travelled 56-76 km round-trip for ART; we aimed to evaluate changes in uptake of HIV-testing, ART coverage and access to ART following decentralisation. Methods: A total of 2124 adults in 1351 households in two parishes closest to Lira Kato HC were interviewed using questionnaires between March and April 2013 and 2123 adults in 1229 households between January and March 2015. Results: Adults reporting HIV-testing in the last year increased from 1077/2124 (50.7%) to 1298/2123 (61.1%) between surveys (p<0.001). ART coverage increased from 74/136 (54.4%) self-reported HIV-positive adults in 2013 to 108/133 (81.2%) in 2015 (p<0.001). Post-decentralisation, 47/108 (43.5%) of those on ART were in care at Lira Kato HC (including 37 new initiations). Most of the remainder (47/61, 77%) started ART prior to any ART provision at Lira Kato HC; the most common reason given for not accessing ART locally was concern about drug-stock-outs (30/59, 51%). Conclusions: HIV-testing and ART coverage increased after decentralisation combined with Option B+ roll-out. However, patients on ART before decentralisation were reluctant to transfer to their local facility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".