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.
DESIGN: We analyzed data from a community-recruited prospective cohort in Vancouver, Canada (n = 623), from 2014 to 2017.
METHODS: We used multivariable generalized mixed-effects analyses to estimate longitudinal factors associated with mean material security score. We then estimated the association between achieving at least 95% adherence to ART and overall mean material score, as well as mean score for three factors derived from a factor analysis. The three-factor structure, employed in the current analyses, were factor 1 (basic needs); factor 2 (housing-related variables) and factor 3 (economic resources).
RESULTS: Recent incarceration [β-coefficient (β) = -0.176, 95% confidence interval (95% CI): -0.288 to -0.063], unmet health needs [β = -0.110, 95% CI: -0.178 to -0.042), unmet social service needs (β = -0.264, 95% CI: -0.336 to -0.193) and having access to social services (β= -0.102, 95% CI: -0.1586 to -0.0465) were among the factors associated with lower material security scores. Contrary to expectations that low levels of material security in this population would lead to poor ART adherence, we did not observe a significant relationship between adherence and overall material security score, or for each factor individually.
CONCLUSION: Our findings highlight the potentially important role of no-cost, universal access to HIV prevention and treatment, in mitigating the impact of socioeconomic disadvantage on ART adherence.
METHODS: In a nationally representative cross-sectional study, soon-to-be released prisoners in Kyrgyzstan (N=368) and Azerbaijan (N=510) completed standardized health assessment surveys. After identifying correlated variables through bivariate testing, we built multi-group path models with pre-incarceration official and unofficial detention as exogenous variables and pre-incarceration composite HIV risk as an endogenous variable, controlling for potential confounders and estimating indirect effects.
RESULTS: Overall, 463 (51%) prisoners reported at least one detention in the year before incarceration with an average of 1.3 detentions in that period. Unofficial detentions (13%) were less common than official detentions (41%). Optimal model fit was achieved (X (2)=5.83, p=0.44; Goodness of Fit Index (GFI) GFI=0.99; Comparative Fit Index (CFI) CFI=1.00; Root Mean Square Error of Approximation (RMSEA) RMSEA=0.00; PCLOSE=0.98) when unofficial detention had an indirect effect on HIV risk, mediated by drug addiction severity, with more detentions associated with higher addiction severity, which in turn correlated with increased HIV risk. The final model explained 35% of the variance in the outcome. The effect was maintained for both countries, but stronger for Kyrgyzstan. The model also holds for Kyrgyzstan using unique data on within-prison drug injection as the outcome, which was frequent in prisoners there.
CONCLUSIONS: Detention by police is a strong correlate of addiction severity, which mediates its effect on HIV risk behaviour. This pattern suggests that police may target drug users and that such harassment may result in an increase in HIV risk-taking behaviours, primarily because of the continued drug use within prisons. These findings highlight the important negative role that police play in the HIV epidemic response and point to the urgent need for interventions to reduce police harassment, in parallel with interventions to reduce HIV transmission within and outside of prison.