Evolution of Primary HIV Drug Resistance in a Subtype C Dominated Epidemic in Mozambique
Bibliographic record
Abstract
OBJECTIVE: In Mozambique, highly active antiretroviral treatment (HAART) was introduced in 2004 followed by decentralization and expansion, resulting in a more than 20-fold increase in coverage by 2009. Implementation of HIV drug resistance threshold surveys (HIVDR-TS) is crucial in order to monitor the emergence of transmitted viral resistance, and to produce evidence-based recommendations to support antiretroviral (ARV) policy in Mozambique. METHODS: World Health Organization (WHO) methodology was used to evaluate transmitted drug resistance (TDR) in newly diagnosed HIV-1 infected pregnant women attending ante-natal clinics in Maputo and Beira to non-nucleoside reverse transcriptase inhibitors (NNRTI), nucleoside reverse transcriptase inhibitors (NRTI) and protease inhibitors (PI). Subtypes were assigned using REGA HIV-1 subtyping tool and phylogenetic trees constructed using MEGA version 5. RESULTS: Although mutations associated with resistance to all three drug were detected in these surveys, transmitted resistance was analyzed and classified as <5% in Maputo in both surveys for all three drug classes. Transmitted resistance to NNRTI in Beira in 2009 was classified between 5-15%, an increase from 2007 when no NNRTI mutations were found. All sequences clustered with subtype C. CONCLUSIONS: Our results show that the epidemic is dominated by subtype C, where the first-line option based on two NRTI and one NNRTI is still effective for treatment of HIV infection, but intermediate levels of TDR found in Beira reinforce the need for constant evaluation with continuing treatment expansion in Mozambique.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".