Large disparities in HIV treatment cascades between eight European and high‐income countries – analysis of break points
Bibliographic record
Abstract
INTRODUCTION: Patients on antiretroviral treatment with undetectable HIV RNA levels have a significantly lower risk of clinical disease progression and onward HIV transmission. This study aimed to estimate and compare the percentage of all HIV-positive people who are diagnosed, are linked to care, are taking antiretroviral treatment and have undetectable HIV RNA, in eight European and high-income countries: the United States, the United Kingdom, France, the Netherlands, Denmark, Australia, British Columbia (Canada) and Georgia. MATERIALS AND METHODS: For each country, the number of people in five key stages of the HIV treatment cascade was collected: 1. HIV infected, 2. Known to be HIV positive, 3. Linked to care, 4. Taking antiretroviral treatment, and 5. Having undetectable HIV RNA. Estimates were extracted from national reports (1-3), the UNAIDS database, conference proceedings (4) and peer-reviewed articles (5-7). The quality of the estimates and reporting methods were assessed individually for each country, with selection criteria such as availability of nationwide database and routinely collected data. Treatment cascades were constructed using estimates from 2010 to 2012. RESULTS: As shown in Table 1, the percentage of all infected people with undetectable HIV RNA ranged from 20% in Georgia to 59% in Denmark. Of the high-income countries, the United States has the lowest percentage of individuals with undetectable viral load (25% to median 52%), associated with the highest HIV incidence rate (15.30 per 100,000 to median 6.07 per 100,000). The pattern of the cascades differed between countries: in the United States, there is a fall from 66% to 33% (-33%) between linkage to care and start of antiretroviral treatment. However, in Georgia, the greatest loss in continuum was zat diagnosis, with 48% of undiagnosed HIV-positive individuals. CONCLUSIONS: There are great disparities among European and high-income countries in the percentage of HIV-positive individual with undetectable HIV RNA. Furthermore, the treatment cascades show different key break points, underlying inequalities in HIV care between countries.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".