Comparing risk environments for HIV among people who inject drugs from three cities in Northern Mexico
Bibliographic record
Abstract
BACKGROUND: A large body of research has investigated the rise of injection drug use and HIV transmission in Tijuana and Ciudad Juarez (CJ). However, little is known about the dynamics of injecting in Hermosillo. This study compares drug-related behaviors and risk environment for HIV of people who inject drugs (PWID) across Tijuana, CJ, and Hermosillo to identify factors that could explain differences in HIV prevalence. METHODS: Data from Tijuana belong to a prospective study (El Cuete IV). Data from Hermosillo and Ciudad Juarez belong to a cross-sectional study. Both studies collected data in places where PWID spend time. All participants completed quantitative behavioral and serological testing for HIV. Datasets were merged using only comparable variables. Descriptive statistics tests were used to compare sociodemographic and behavioral characteristics of people who inject drugs PWID sampled in each city. A logistic regression model was built to identify factors independently associated with the likelihood of reporting receptive syringe sharing in the past 6 months. RESULTS: A total of 1494 PWID provided data between March 2011 and May 2012. HIV prevalence differed significantly between participants in Tijuana (4.2%), CJ (7.7%), and Hermosillo (5.2%; p < 0.05). PWID from Hermosillo reported better living conditions, less frequency of drug injection, and lower prevalence of syringe sharing (p < 0.01). PWID from CJ reported a higher prevalence of syringe sharing and confiscation by police (p < 0.01). In a multivariable logistic regression model, living in Hermosillo compared to Tijuana (adjusted odds ratio [AOR] = 0.42, 95% confidence interval [CI] 0.29-0.61) and being female (AOR = 0.61, 95% CI 0.45-0.83) were protective against syringe sharing. Having used crystal meth (AOR = 1.62, 95% CI 1.24-2.13, p = 0.001), having experienced syringe confiscation by police in the last 6 months (AOR = 1.78, 95% CI 1.34-2.40), and lower perception of syringe availability (AOR = 2.15, 95% CI 1.59-2.91) were significantly associated with syringe sharing (p < 0.05). CONCLUSIONS: Differences in HIV prevalence across cities reflect mainly differences in risk environments experienced by PWID, shaped by police practices, access to injection equipment, and dynamics of drug markets. Findings highlight the importance of ensuring sterile syringe availability through harm reduction services and a human rights approach to drug harms in northern Mexico and to generate better understanding of local dynamics and contexts of drug use for designing proper harm reduction programs.
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 | 0.000 |
| 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 | 0.001 |
| 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".