Prevalence and risk factors for HIV-1 infection in people who use illicit drugs in northern Brazil
Bibliographic record
Abstract
BACKGROUND: People who use illicit drugs (PWUDs) have a high risk of viral infections. To date, there is a paucity of information on HIV infection among PWUDs in remote Brazilian regions. This study determined the prevalence and factors associated with HIV-1 infection among PWUDs in northern Brazil. METHODS: Sociodemographic, economic, drug use and health-related information were collected through interviews from a community-recruited, multi-site sample of 1753 PWUDs. The blood samples collected were tested for the presence of HIV-1 using chemiluminescence immunoassay and PCR or western blotting. Logistic regressions identified factors independently associated with HIV-1 infection. RESULTS: In total, 266 (15.2%) PWUDs were HIV-1 positive. Hepatitis B virus and/or hepatitis C virus nucleic acid was detected in 65 (3.7%) PWUDs infected by HIV-1. The factors associated with HIV-1 infection were male gender, older age, a lower educational level and a lower income, crack cocaine use, a longer drug use history and a history of drug injection and engagement in unsafe sex, sex work and a higher number of sexual partners. CONCLUSIONS: The current study provides unique, initial insights into HIV and co-infection status and pertinent risk factors among PWUDs in northern Brazil, with clear and diverse implications for urgently improved prevention and treatment intervention needs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".