Can the combination of TasP and PrEP eliminate HIV among MSM in British Columbia, Canada?
Bibliographic record
Abstract
In British Columbia (BC), the HIV epidemic continues to disproportionally affect the gay, bisexual and other men who have sex with men (MSM). In this study, we aimed to evaluate how Treatment as Prevention (TasP) and pre-exposure prophylaxis (PrEP), if used in combination, could lead to HIV elimination in BC among MSM. Considering the heterogeneity in HIV transmission risk, we developed a compartmental model stratified by age and risk-taking behaviour for the HIV epidemic among MSM in BC, informed by clinical, behavioural and epidemiological data. Key outcome measures included the World Health Organization (WHO) threshold for disease elimination as a public health concern and the effective reproduction number (Re). Model interventions focused on the optimization of different TasP and PrEP components. Sensitivity analysis was done to evaluate the impact of sexual mixing patterns, PrEP effectiveness and increasing risk-taking behaviour. The incidence rate was estimated to be 1.2 (0.9–1.9) per 1000 susceptible MSM under the Status Quo scenario by the end of 2029. Optimizing all aspects of TasP and the simultaneous provision of PrEP to high-risk MSM resulted in an HIV incidence rate as low as 0.4 (0.3–0.6) per 1000 susceptible MSM, and an Re as low as 0.7 (0.6–0.9), indicating that disease elimination was possible when TasP and PrEP were combined. Provision of PrEP to younger MSM or high-risk and younger MSM resulted in a similar HIV incidence rate, but an Re with credible intervals that crossed one. Further optimizing all aspects of TasP and prioritizing PrEP to high-risk MSM can achieve the goal of disease elimination in BC. These results should inform public health policy development and intervention programs that address the HIV epidemic in BC and in other similar settings where MSM are disproportionately affected.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".