METHODS: Data were derived from a respondent-driven survey sample (RDS) collected during 2010 of 460 PWID in greater Kuala Lumpur. Analysis focused on socio-demographic, clinical, behavioural, and network information. Spatial probit models were developed based on a distinction between the influence of peers (individuals nominated through a recruitment network) and neighbours (residing a close distance to the individual). The models were expanded to account for the potential influence of the network formation.
RESULTS: Recruitment patterns of HIV-infected PWID clustered both spatially and across the recruitment networks. In addition, HIV-infected PWID were more likely to have peers and neighbours who inject with clean needles were HIV-infected and lived nearby (<5km), more likely to have been previously incarcerated, less likely to use clean needles (26.8% vs 53.0% of the reported injections, p<0.01), and have fewer recent injection partners (2.4 vs 5.4, p<0.01). The association between the HIV status of peers and neighbours remained significantly correlated even after controlling for unobserved variation related to network formation and sero-sorting.
CONCLUSION: The relationship between HIV status across networks and space in Kuala Lumpur underscores the importance of these factors for surveillance and prevention strategies, and this needs to be more closely integrated. RDS can be applied to identify injection network structures, and this provides an important mechanism for improving public health surveillance, accessing high-risk populations, and implementing risk-reduction interventions to slow HIV transmission.
Materials and Methods: Randomly selected HIV-infected male prisoners (n=102) from two prisons in Jakarta, Indonesia completed surveys in prison and were followed up for 2 years (until study completion) or until they died or were lost to follow-up. Death dates were determined from medical records and interviews with immediate family members. Kaplan-Meier and Cox proportional hazards regression models were analyzed to identify mortality predictors.
Results: During 103 person-years (PYs) of follow-up, 15 deaths occurred, including ten in prison. The crude mortality rate within prison (125.2 deaths per 1,000 PYs) was surpassed by the crude mortality rate in released prisoners (215.7 deaths per 1,000 PYs). HIV-associated opportunistic infections were the most common probable cause of death. Predictors of within-prison and overall mortality were similar. Shorter survival overall was associated with being incarcerated within a specialized "narcotic" prison for drug offenders (hazard ratio [HR] 9.2, 95% confidence interval [CI] 1.1-76.5; P=0.03), longer incarceration (HR 1.06, 95% CI 1.01-1.1; P=0.01), and advanced HIV infection (CD4+ T-cell count<200cells/μL; HR 4.8, 95% CI 1.2-18.2; P=0.02). Addiction treatment was associated with longer survival (HR 0.1, 95% CI 0.01-0.9; P=0.03), although treatment with antiretroviral therapy (ART) or methadone was not.
Conclusions: Mortality in HIV-infected prisoners is extremely high in Indonesia, despite limited provision of ART in prisons. Interventions to restore immune function with ART and provide prophylaxis for opportunistic infections during incarceration and after release would likely reduce mortality. Narcotics prisons may be especially high-risk environments for mortality, emphasizing the need for universal access to evidence-based HIV treatments.
METHODS: This study prospectively evaluated mortality after prison release and whether methadone initiated before release increased survival after release in a sample of men with HIV and OUD (n = 291). We linked national death records to data from a controlled trial of prerelease methadone initiation conducted from 2010 to 2014 with men with HIV and OUD imprisoned in Malaysia. Vital statistics were collected through 2015. Allocation to prerelease methadone was by randomization (n = 64) and participant choice (n = 246). Cox proportional hazards models were used to estimate treatment effects of prerelease methadone on postrelease survival.
RESULTS: Overall, 62 deaths occurred over 872.5 person-years (PY) of postrelease follow-up, a crude mortality rate of 71.1 deaths per 1000 PY (95% confidence interval [CI] 54.5-89.4). Most deaths were of infectious etiology, mostly related to HIV. In a modified intention-to-treat analysis, the impact of prerelease methadone on postrelease mortality was consistent with a null effect in unadjusted (hazard ratio [HR] 1.3, 95% CI 0.6-3.1) and covariate-adjusted (HR 1.2, 95% CI 0.5-2.8) models. Predictors of mortality were educational level (HR 1.4, 95% CI 1.0-1.8), pre-incarceration alcohol use (HR 2.0, 95% CI 1.1-3.9), and lower CD4+ T-lymphocyte count (HR 0.8 per 100-cell/mL increase, 95% CI 0.7-1.0).
CONCLUSIONS: Postrelease mortality in this sample of men with HIV and OUD was extraordinarily high, and most deaths were likely of infectious etiology. No effect of prerelease methadone on postrelease mortality was observed, which may be due to study limitations or an epidemiological context in which inadequately treated HIV, and not inadequately treated OUD, is the main cause of death after prison release.
TRIAL REGISTRATION: NCT02396979. Retrospectively registered 24/03/2015.
METHODS: From 2010 to 2014, men with HIV (N = 212) and opioid dependence before incarceration were enrolled in MMT within 6 months of release from Malaysia's largest prison and followed for 12-months post-release. As a prospective trial, allocation to MMT was at random and later by preference design (predictive nonetheless). MMT dosing was individually targeted to minimally achieve 80 mg/day. Time-to-event analyses were conducted to model linkage to MMT after release.
FINDINGS: Of the 212 participants allocated to MMT, 98 (46 %) were prescribed higher dosages (≥80 mg/day) before release. Linkage to MMT after release occurred in 77 (36 %) participants and significantly higher for those prescribed higher dosages (46% vs 28 %; p = 0.011). Factors associated with higher MMT dosages were being married, on antiretroviral therapy, longer incarceration periods, having higher levels of depression, and methadone preference compared to randomization. After controlling for other variables, being prescribed higher methadone dosage (aHR: 2.53, 95 %CI: 1.42-4.49) was the only independent predictor of linkage to methadone after release.
INTERPRETATION: Higher doses of methadone prescribed before release increased the likelihood of linkage to MMT after release. Methadone dosing should be introduced into international guidelines for treatment of opioid use disorder in prisons and further post-release benefits should be explored.
FUNDING: National Institute of Drug Abuse (NIDA).