Expanding HAART Treatment to All Currently Eligible Individuals under the 2008 IAS-USA Guidelines in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: In 2008, the IAS-USA published the revised guidelines for the use of HAART in adults substantially increasing the number of individuals eligible for HAART. The epidemic in British Columbia (BC) is mainly among men who have sex with men and those with injection drug use. Here, we explored the potential impact of different HAART coverage scenarios, based on the new guidelines, on the HIV-related incidence, morbidity and mortality in BC, Canada. METHODOLOGY: We built a mathematical transmission model to investigate different HAART coverage scenarios (50%, 60%, 75% and 100%) of those medically eligible to receive HAART under the 2008 IAS guidelines. All new scenarios were compared to the current coverage in BC under the 2006 IAS guidelines (i.e. baseline scenario). In BC, it is estimated that 25-30% of individuals are unaware of their status. Costs were drug-related and reported in Canadian dollars. HIV-related morbidity and mortality were estimated based on the disability-adjusted life years (DALY) methodology. PRINCIPAL FINDINGS: Currently, there are 4379 individuals on HAART under the IAS 2006 guidelines and 6781 individuals who qualify for treatment based on the new guidelines. Within 5 years, increasing HAART coverage decreased yearly new infections by at least 44.8%. In the 50% scenario, in 5 years, DALY decreased by 53% corresponding to 4155 averted DALYs, and in 25 years it decreased by 66% corresponding to 5837 averted DALYs. The effect was even stronger if the 75% scenario was chosen instead. Compared to the 100% expansion scenario, we observed an excess in annual direct treatment expenditures at the end of 5 years of approximately 1 million dollars in the 75% scenario, and of approximately 2 million dollars in the 50% scenario. CONCLUSIONS/SIGNIFICANCE: The individual and public health benefits of these new guidelines are immense. The results show that by increasing the number of individuals on HAART save lives, it is cost averting, and it positively impacts society by decreasing the number of new HIV infections. Thus, public health community should consider incremental gains when considering guidelines and policy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".