World Health Organization surveys to monitor HIV drug resistance prevention and associated factors in sentinel antiretroviral treatment sites
Bibliographic record
Abstract
The World Health Organization (WHO) estimates that >2 million people will have started antiretroviral therapy (ART) by the end of 2006. As the development of some HIV drug resistance (HIVDR) is inevitable in populations taking ART, the emergence of HIVDR must be balanced against the benefits of providing ART, including improved health outcomes and decreased HIV/AIDS-associated morbidity and mortality. ART programmes should operate to minimize the emergence of HIVDR in populations receiving therapy and HIVDR itself must be monitored to ensure ongoing regimen efficacy. ART regimens in resource-limited settings are usually selected at the national level following a public health approach: generally only one first-line regimen with alternate regimen(s) incorporating within-class drug substitutions are available in the public sector. The WHO has developed a population-based HIVDR assessment and prevention strategy, which includes standardized HIVDR monitoring surveys in populations receiving first-line ART at sentinel sites. The WHO surveys monitor HIVDR prevention in sentinel sites by utilizing a standardized, minimum-resource prospective survey methodology to assess the success of adult and paediatric ART sites in preventing HIVDR emergence during the first year of ART. The surveys also identify associated factors that can be addressed at the level of the ART site or programme. WHO HIVDR monitoring surveys are designed to be integrated easily into a country's ongoing, routine HIV-related evaluation activities. Performed regularly at representative sites, the data generated will inform evidence-based decision making regarding national and global ART regimen selection and minimize the emergence of HIVDR at a population level.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".