The Lablite project: A cross-sectional mapping survey of decentralized HIV service provision in Malawi, Uganda and Zimbabwe
Bibliographic record
Abstract
BACKGROUND: In sub-Saharan Africa antiretroviral therapy (ART) is being decentralized from tertiary/secondary care facilities to primary care. The Lablite project supports effective decentralization in 3 countries. It began with a cross-sectional survey to describe HIV and ART services. METHODS: 81 purposively sampled health facilities in Malawi, Uganda and Zimbabwe were surveyed. RESULTS: The lowest level primary health centres comprised 16/20, 21/39 and 16/22 facilities included in Malawi, Uganda and Zimbabwe respectively. In Malawi and Uganda most primary health facilities had at least 1 medical assistant/clinical officer, with average 2.5 and 4 nurses/midwives for median catchment populations of 29,275 and 9,000 respectively. Primary health facilities in Zimbabwe were run by nurses/midwives, with average 6 for a median catchment population of 8,616. All primary health facilities provided HIV testing and counselling, 50/53 (94%) cotrimoxazole preventive therapy (CPT), 52/53 (98%) prevention of mother-to-child transmission of HIV (PMTCT) and 30/53 (57%) ART management (1/30 post ART-initiation follow-up only). All secondary and tertiary-level facilities provided HIV and ART services. In total, 58/81 had ART provision. Stock-outs during the 3 months prior to survey occurred across facility levels for HIV test-kits in 55%, 26% and 9% facilities in Malawi, Uganda and Zimbabwe respectively; for CPT in 58%, 32% and 9% and for PMTCT drugs in 26%, 10% and 0% of facilities (excluding facilities where patients were referred out for either drug). Across all countries, in facilities with ART stored on-site, adult ART stock-outs were reported in 3/44 (7%) facilities compared with 10/43 (23%) facility stock-outs of paediatric ART. Laboratory services at primary health facilities were limited: CD4 was used for ART initiation in 4/9, 5/6 and 13/14 in Malawi, Uganda and Zimbabwe respectively, but frequently only in selected patients. Routine viral load monitoring was not used; 6/58 (10%) facilities with ART provision accessed centralised viral loads for selected patients. CONCLUSIONS: Although coverage of HIV testing, PMTCT and cotrimoxazole prophylaxis was high in all countries, decentralization of ART services was variable and incomplete. Challenges of staffing and stock management were evident. Laboratory testing for toxicity and treatment effectiveness monitoring was not available in most primary level facilities.
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How this classification was reachedexpand
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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".