IntroductionProviding HIV healthcare and Treatment as Prevention both depend on diagnosing HIV cases, preferably soon after initial infection. We hypothesized that tracing risk networks recruits higher proportions of undiagnosed positives than outreach‐based testing or respondent‐driven sampling (RDS) in Odessa, Ukraine.MethodsThe Transmission Reduction Intervention Project (TRIP) used risk network tracing to recruit sexual and injection networks of recently‐infected and longer‐term infected (LTs) seeds (2013 to 2016). Integrated Biobehavioural Surveillance (IBBS) (2013) used RDS to recruit people who inject drugs (PWID). Outreach Testing tested PWID for HIV at community outreach sites (2013 to 2016). Proportions of undiagnosed positives among those tested were compared TRIP versus IBBS; TRIP versus Outreach Testing and between TRIP arms. Costs were compared across the projects.Results TRIP tested 1252 people (21% women) in seeds’ risk networks; IBBS tested 400 (18% women); Outreach Testing 13,936 (31% women). TRIP networks included a higher proportion of undiagnosed positives (14.6%) than IBBS (5.0%) or Outreach Testing (2.4%); odds ratio (OR) 3.25 (95% CI 2.07, 5.12) versus IBBS and 7.03 (CI 5.95, 8.31) versus Outreach Testing respectively. Findings remained significant in analyses stratified by sex and when PWID in TRIP networks were compared with Outreach Testing and IBBS. Within TRIP, recently‐infected participants’ networks contained higher proportions of undiagnosed positives (16.3%) than LTs’ networks (12.2%); OR 1.41 (CI 1.01, 1.95). TRIP located undiagnosed positives less expensively than did RDS or Outreach Testing.Conclusions TRIP's recruiting techniques, including prioritizing networks of the recently infected, find undiagnosed HIV‐positive people efficiently. They should be integrated with standard practice to improve case‐finding. Research should test these techniques in other socio‐epidemiologic contexts.Clinical trial registryRegistered ClinicalTrials.gov: NCT01827228.

Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013–2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic’s effective reproductive number (Re) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06–0.75), but not in Kyiv (Re = 2.3, 95%HPD 0.2–5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013–2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.

Introduction This paper examines the extent to which an intervention succeeded in locating people who had recently become infected with HIV in the context of the large‐scale Ukrainian epidemic. Locating and intervening with people who recently became infected with HIV (people with recent infection, or Pw RI ) can reduce forward HIV transmission and help Pw RI remain healthy. Methods The Transmission Reduction Intervention Project ( TRIP ) recruited recently‐infected and longer‐term infected seeds in Odessa, Ukraine, in 2013 to 2016, and asked them to help recruit their extended risk network members. The proportions of network members who were Pw RI were compared between TRIP arms (i.e. networks of recently‐infected seeds vs. networks of longer‐term infected seeds) and to the proportion of participants who were Pw RI in an RDS ‐based Integrated Biobehavioral Surveillance of people who inject drugs in 2013. Results The networks of Pw RI seeds and those of longer‐term infected seeds had similar (2%) proportions who were themselves Pw RI . This was higher than the 0.25% proportion in IBBS ( OR = 7.80; p = 0.016). The odds ratio among the subset of participants who injected drugs was 11.17 ( p = 0.003). Cost comparison analyses using simplified ingredients‐based methods found that TRIP spent no more than US $4513 per Pw RI located whereas IBBS spent $11,924. Conclusions Further research is needed to confirm these results and improve TRIP further, but our findings suggest that interventions that trace the networks of people who test HIV ‐positive are a cost‐effective way to locate Pw RI and reduce HIV transmission and should therefore be implemented.

Molecular methods can identify HIV-infected people socially linked with another person in about half of the phylogenetic clusters. This could help public health efforts to locate individuals in networks with high transmission rates.

It also reviews what network research has discovered about how network characteristics are associated with HIV and other infections, risk behaviors, preventive behaviors, and care, and discusses some ways in which network-based public health interventions have been conducted. Based on this, risk and social network research and interventions seem both feasible and valuable for addressing the many public health and social problems raised by the widespread use of opioids in the US South.