Can platform use patterns be an indicator of HIV-related risk and sub-group heterogeneity among men who have sex with men in Singapore: a latent class analysis.

Introduction: Low-level HIV epidemic settings like Singapore face the challenge of reaching men at-risk who have less contact with programmes. We investigated patterns of meeting platform use by men seeking male sexual partners (MSM) as potential marker of risk to differentiate sub-groups for interventions. Methods: Latent Class Analysis (LCA) was applied to a survey sample of MSM recruited from bars/clubs, saunas and a smartphone application, using purposive sampling. The best-fit LCA model which identified homogeneous sub-groups with similar patterns of meeting platform was factored in multivariable regression to identify associations with risk behaviors on the pathway to HIV infection. Results: Overall 1,141 MSM were recruited from bars/clubs (n = 426), saunas (n = 531), and online (n = 184). Five patterns emerged, reflecting salient platform use characteristics: Sauna-centric (SC; n = 413), App-centric (AC; n = 276), Multiple-platforms (MP; n = 123), Platform-inactive (PI; n = 257), and "Do not hook up" (DNH; n = 72) classes. Men in the SC and MP classes had high probabilities of using saunas to meet partners; SC were older and less likely to have disclosed their sexual orientation. The MP class had high probabilities of connecting across all platforms in addition to saunas and more likely to have disclosed their sexual orientation, than the PI class. Men in the SC and MP classes had twice the odds of reporting multiple sex partners (aORSC = 2.1; 95%CI: 1.33.2; aORMP = 2.2; 95%CI: 1.14.6). Single/non-partnered MSM and those using alcohol/drugs during sex had 1.7 (95%CI: 1.22.5) and 3.2 (95%CI: 2.05.1) the odds respectively, of reporting multiple sex partners. The SC and MP classes had higher odds of engaging in group sex while MSM using alcohol/drugs during sex had twice the odds of reporting group sex. Alcohol/drugs and group sex were independently associated with condomless sex (as was lower education). Group sex, alcohol/drugs during sex, disclosure of sexual orientation or being Singaporean/permanent resident were associated with recent testing for HIV. Discussion: The five distinct risk profiles identified can help tailor differentiated HIV interventions-combined with field knowledge and other prevention-to expand HIV self-testing, Pre-Exposure Prophylaxis and other services (e.g., Mpox vaccination) to sub-groups at risk.

Can a multi-level intervention approach, combining behavioural disciplines, novel technology and incentives increase physical activity at population-level?

BACKGROUND: Despite a global call for action and growing burden of non-communicable diseases (NCD) associated with physical inactivity, effective interventions to increase community-wide physical activity (PA) remain few. NCDs accounted for 80% of Singapore's disease burden (2015) and yet 40% of Singaporeans did not meet minimum recommended weekly PA despite evidence of the benefits to cardiorespiratory health, diabetes and cancer prevention. METHODS: A large-scale public health intervention was initiated in 2015 to increase population-level PA through incidental daily walking. Intervention components included fitness trackers, redeemable rewards and gamification, implemented in a mutually-reinforcing manner within an eco-system supportive of PA and informed by real-time data analytics. Mean daily step count at baseline and post-intervention were compared across periods, and the influence of participant sub-groups characteristics on overall results, using significance tests. Standards for Reporting on Implementation Studies (StaRI) were adhered to. RESULTS: Intervention reach increased fourfold from 129,677 participants in wave 1 (2015-16) to 690,233 in wave 3 (2017-18) amounting to a total of 1,184,410 Step Challenge participations. Mean days of fitness tracker use increased from 2.4 to 5.0 days/week among participants completing the Challenge in wave 1 and from 5.3 to 6.0 days/week in wave 3. The mean number of daily steps between pre-Challenge and Challenge periods increased by 4163 (sd=1360; p< 0.001) in wave 1, by 2242 (sd=334; p< 0.001) in wave 2 and by 1645 steps/day (sd=54; p< 0.001) in wave 3. Mean daily step increases between wave 1 and 3 also suggest that incidental PA was maintained, a finding supported by a 2017 national population survey showing that incidental PA among adults increased from 5% in 2010 to 14% in 2017 while moderate-intensity PA increased from 5 to 10% over the same period. CONCLUSION: Population-level PA was effectively increased through multi-level interventions integrating technology, behavioural economics, gamification, marketing, communications and community linkages within a supportive context- and climate-appropriate environment. Responsive data analytics were instrumental to strengthen implementation by tailoring modalities that maximise effectiveness at population-level. Further analyses are needed to explore potential barriers, challenges or unmet needs in sub-groups with lower uptake to tailor future interventions for greater reach and impact.

Differences in risk behaviours and HIV status between primary amphetamines and opioid injectors in Estonia and Russia.

BACKGROUND AND OBJECTIVE: People who inject drugs (PWID) account for over half of new HIV infections in Eastern Europe and central Asia, where opioids continue to be the dominant illicit drugs injected. Stimulants including amphetamines (ATS) have been associated with HIV infection risk in several settings. We sought to examine whether primary ATS injection was associated with greater HIV risk, compared to opioid injection in two European locales with significant HIV epidemics. METHODS: PWID in Kohtla-Järve and St. Petersburg were recruited using respondent-driven sampling in 2012-2013. Survey data on demographic characteristics, service use, injecting and sexual risk behaviours and HIV-status (and HCV in Kohtla-Järve) were compared between primary opioid and ATS injectors using logistic regression models. RESULTS: Of 591 injectors recruited in Kohtla-Järve and 811 in St. Petersburg, 195 (33%) and 27 (4%) primarily injected ATS in each city. In both cities, ATS injectors were younger than opioid injectors, initiated injection later, injected less frequently and were more likely to have been paid for sex. In both cities, PWID had high levels of multiple sex partners. In Kohtla-Järve, ATS-injectors had lower odds of back-loading and greater odds of polydrug use than opioid-injectors. In St. Petersburg, where over half of PWID reported unsafe sharing practices, ATS-injectors were less likely to report these practices. ATS-injection was negatively associated with being HIV positive in Kohtla-Järve (aOR = 0.6; 95%CI: 0.5-0.8) and St. Petersburg (aOR = 0.3; 95%CI: 0.1-0.7). ATS-injection was negatively associated with HCV-reactivity in Kohtla-Järve (aOR = 0.5; 95%CI: 0.3-0.6). CONCLUSIONS: In both locations, primary ATS injection was associated with lower injecting risk behaviours, lower odds of HIV and being paid for sex compared to opioid injection. Interventions targeting the characteristics and needs of ATS injectors are needed to increase contact with services and reduce sexual and injecting risk. Harm reduction services, including sexual risk reduction, need to be expanded for all PWID in St. Petersburg.

Polydrug Use and Heterogeneity in HIV Risk Among People Who Inject Drugs in Estonia and Russia: A Latent Class Analysis.

Non-medical drug injection is a major risk factor for HIV infection in Russia and Estonia. Multiple drug use (polydrug) has further been associated with increased harms. We compared HIV, injecting and sexual risk associated with polydrug use among people who injected drugs (PWID) in 2012-2013 in Kohtla-Järve (Estonia, n = 591) and St Petersburg (Russia, n = 811). Using latent class analysis, we identified five (poly)drug classes, the largest consisting of single-drug injectors among whom an opioid was the sole drug injected (56% of PWID). The four remaining polydrug classes included polydrug-polyroute injectors who injected and used opiates and stimulants (9%), opiate-stimulant poly-injectors who injected amphetamine-type-stimulants with a primary opiate (7%) and opiate-opioid poly-injectors who injected opioids and opiates (16%). Non-injection stimulant co-users were injectors who also used non-injection stimulants (12%). In multivariable multinomial regressions, all four polydrug classes were associated with greater injection risks than single-drug injection, while opiate-stimulant and opiate-opioid poly-injection were also associated with having multiple sex partners. Riskier behaviours among polydrug-injectors suggest increased potential for transmission of blood-borne and sexually-transmitted infections. In addition to needles/syringes provision, services tailored to PWID drug and risk profiles, could consider drug-appropriate treatment and sexual risk reduction strategies to curb HIV transmission.

Influence of different drugs on HIV risk in people who inject: systematic review and meta-analysis.

AIMS: To assess systematically the risk of HIV acquisition by type of drug injected across different settings. METHODS: A systematic review and meta-analysis were conducted. Databases were searched for studies of HIV incidence in people who inject different drugs (PWID). Pooled HIV incidence rate ratio (IRR) was used to compare HIV risk between injecting and not-injecting a given drug, when possible, or otherwise with those reported not to have injected the substance. Pooled estimates of crude IRR were derived using random-effects models. Variations in IRR were assessed in subgroup analyses, by drug and geographical region. RESULTS: Of 5779 studies screened, 15 were included. HIV incidence was reported for people injecting cocaine (eight: North America, Europe), amphetamine-type stimulants (ATS) (four: Western and Eastern Europe, Asia), heroin (11: all settings), opiate-stimulants (four: North America, Western and Eastern Europe) and opiates-sedatives (five: Europe, Asia). HIV risk in cocaine injectors was 3.6 times 95% confidence interval (CI) = 2.8-4.7, I(2) = 0%; n = 4) that of non-injectors and 3.0 for ATS injectors (95% CI = 2.2-4.1, I(2) = 0%; n = 2). Higher sexual risk was reported in cohorts injecting stimulants. Compared to not-injecting, HIV IRR was 2.8 (95% CI = 1.7-4.7, I(2) = 77%; n=6) for all heroin injectors and 3.5 (95% CI = 2.3-5.2, I(2) = 40%; n=5) for heroin injectors in Asia and Europe. CONCLUSION: The risk of HIV acquisition in people who inject drugs appears to vary by drug type but differences are not statistically significant, precluding conclusive grading of risk.