Heterogeneous impacts of HIV pre-exposure prophylaxis (PrEP) on drug resistance and phylogenetic cluster transmission dynamics in British Columbia, Canada: A retrospective cohort and simulation study
Bibliographic record
Abstract
BACKGROUND: HIV pre-exposure prophylaxis (PrEP) prevents infection when used during periods of risk, however, its population-level effectiveness is hindered by incomplete uptake, adherence, and retention. Since oral PrEP became available free-of-cost in British Columbia (BC), Canada, in January 2018, uptake has been rapid among eligible individuals, primarily comprising gay, bisexual, and other men who have sex with men (GBM), however, its effectiveness against HIV acquisition across subpopulations alongside potential effects on baseline drug resistance have not been estimated. We evaluated individual and population-level impacts of PrEP on HIV drug resistance and transmission in phylogenetic clusters, representing groups of individuals linked by recent outbreaks, to elucidate heterogeneity in its effectiveness. METHODS AND FINDINGS: Using a retrospective cohort design, we evaluated the frequencies of baseline drug resistance mutations and membership in phylogenetic clusters among newly HIV diagnosed people who ever filled a prescription for HIV PrEP (i.e., PrEP users) in BC (n = 39) compared to non-PrEP users (n = 566) diagnosed from 2018 to 2022 in the BC Drug Treatment Program with at least one sequence available. Newly HIV diagnosed PrEP users were significantly more likely than newly diagnosed non-PrEP users to be included in phylogenetic clusters (chi-squared test, p = 0.0075) and carry baseline nucleoside analogue reverse transcriptase inhibitor (NRTI) resistance mutation M184I/V (Fisher's exact test, adjusted p-value = 0.025). Subsequently, we quantified the population-level impacts of widespread PrEP availability on transmission based on the effective reproduction number (Re), compared across key populations living with HIV in BC and active phylogenetic clusters with at least one new case since 2018. We applied simulations of active clusters' growth based on their empirically observed Re with or without estimated PrEP impacts to estimate diagnoses averted via PrEP across clusters, with non-clustered cases grouped together. Most diagnoses were averted in large and medium GBM-predominant clusters. In a Poisson model, clusters with fewer diagnoses averted were associated with having a higher median age and lower proportion of new diagnoses with PrEP use, adjusted for cluster size at the end of 2017 and proportion residing in Vancouver Coastal Health Authority. These results must be interpreted in light of uncertainty owing to incomplete sampling, the use of consensus genomes, phylogenetic inference, and the assumptions of counterfactual simulations. CONCLUSIONS: We estimated that the oral PrEP program in BC from 2018 to 2022 averted approximately 20 new HIV diagnoses per year across phylogenetic clusters, while infrequently contributing to baseline drug resistance in instances where PrEP was inadvertently prescribed during acute infection or with incomplete adherence. These findings corroborate the broad effectiveness of PrEP, describe heterogeneity in its impacts on clusters' growth, and suggest groups for prioritized PrEP services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".