The population impact of eliminating homelessness on HIV viral suppression among people who use drugs
Bibliographic record
Abstract
OBJECTIVE: We sought to estimate the change in viral suppression prevalence if homelessness were eliminated from a population of HIV-infected people who use drugs. DESIGN: Community-recruited prospective cohort of HIV-infected people who use drugs in Vancouver, Canada. Behavioural information was collected at baseline and linked to a province-wide HIV/AIDS treatment database. The primary outcome was viral suppression (<50 copies/ml) measured during subsequent routine clinical care. METHODS: We employed an imputation-based marginal modelling approach. First, we used modified Poisson regression to estimate the relationship between homelessness and viral suppression (adjusting for sociodemographics, substance use, addiction treatment, and other confounders). Then, we imputed an outcome probability for each individual while manipulating the exposure (homelessness). Population viral suppression prevalence under realized and 'housed' scenarios were obtained by averaging these probabilities across the study population. Bootstrapping was conducted to calculate 95% confidence limits. RESULTS: Of 706 individuals interviewed between January 2005 and December 2013, the majority were men (66.0%), of white race/ethnicity (55.1%), and had a history of injection drug use (93.6%). At first study visit, 223 (31.6%) reported recent homelessness, and 37.8% were subsequently identified as virally suppressed. Adjusted marginal models estimated a 15.1% relative increase [95% confidence interval (CI) 9.0-21.7%) in viral suppression in the entire population - to 43.5% (95% CI 39.4-48.2%) - if all homeless individuals were housed. Among those homeless, eliminating this exposure would increase viral suppression from 22.0 to 40.1% (95% CI 35.1-46.1%), an 82.3% relative increase. CONCLUSION: Interventions to house homeless, HIV-positive individuals who use drugs could significantly increase population viral suppression. Such interventions should be implemented as a part of renewed HIV/AIDS prevention and treatment efforts.
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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 | 0.001 | 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 | 0.001 | 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".