Participation pattern of methadone users and its association with social connection and HIV status: Analyses of electronic health records data

Abstract

Background: HIV spread in injecting drug users (IDU) occurs efficiently between individuals within their social networks. While methadone maintenance treatment has long known to be effective in combating HIV transmission in IDU, the impacts of one's social connections and HIV status have not been well characterised. A study was conducted with the objective of differentiating the pattern of treatment participation between HIV-positive and negative methadone users and to understand its association with social connections with peers.

Methods: Attendance data in one calendar year were extracted from a territory-wide electronic clinical record database of over 8000 methadone users attending 19 clinics in Hong Kong, a city with a relatively low HIV prevalence in injecting drug users. A case-control design was used by matching HIV positive methadone users with HIV negative controls. A temporal-social co-occurrence approach was adopted to construct a social network. Multiple logistic regression and network-based analyses were conducted.

Results: In 2016, a total of 8332 methadone users had attended a clinic at least once, giving 1694016 attendance records that were included in the study. Some 432 methadone, 54 of whom HIV positive, were included in the case-control analyses. Multivariable logistic regression model showed that HIV-positive status was associated with drug injection history (adjusted odds ratio [aOR] 2.28, 95% confidence interval [95% CI] 1.19-4.38), not working fulltime (aOR 3.34, 95% CI 1.15-9.72), ethnic minority (aOR 2.59, 95% CI 1.33-5.02) and minimum daily dose of at least 20mg (aOR 3.64, 95% CI 1.08-12.26). Those having connections with other peers were older (aOR 1.02, 95% CI 1.00-1.04), had a higher mode dose (aOR 1.03, 95% CI 1.02-1.04) and had been admitted to methadone programme for longer time (aOR 1.07, 95% CI 1.02-1.13). Among those with connections, HIV-negative users did not have more connections (median degree centrality 21.00 vs 34.50, p = 0.26) but the network structure was stronger (clustering coefficient 0.65 vs 0.53, p = 0.03).

Conclusion: The weak and sparse linkages may explain the generally low HIV prevalence and incidence in opioid-dependent persons in Hong Kong. Social support could play a constructive role in harm reduction and ethnic minority community-based organisations could help and reinforce treatment adherence.

Fig 1. Algorithm for spatial-temporal social network construction.

Fig 2. Social connections between methadone users.