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A growing body of evidence suggests that network-based interventions to reduce HIV transmission and/or improve HIV-related health outcomes have an important place in public health efforts to move towards 90–90–90 goals. However, the social processes involved in network-based recruitment may pose a risk to participants of increasing HIV-related stigma if network recruitment causes HIV status to be assumed, inferred, or disclosed. On the other hand, the social processes involved in network-based recruitment to HIV testing may also encourage HIV-related social support. Yet despite the relevance of these processes to both network-based interventions and to other more common interventions (e.g., partner services), there is a dearth of literature that directly examines them among participants of such interventions. Furthermore, both HIV-related stigma and social support may influence participants' willingness and ability to recruit their network members to the study. This paper examines (1) the extent to which stigma and support were experienced by participants in the Transmission Reduction Intervention Project (TRIP), a risk network-tracing intervention aimed at locating recently HIV-infected and/or undiagnosed HIV-infected people and linking them to care in Athens, Greece; Odessa, Ukraine; and Chicago, Illinois; and (2) whether stigma and support predicted participant engagement in the intervention. Overall, experiences of stigma were infrequent and experiences of support frequent, with significant variation between study sites. Experiences and perceptions of HIV-related stigma did not change significantly between baseline and six-month follow-up for the full TRIP sample, and significantly decreased during the course of the study at the Chicago site. Experiences of HIV-related support significantly increased among recently-HIV-infected participants at all sites, and among all participants at the Odessa site. Both stigma and support were found to predict participants' recruitment of network members to the study at the Athens site, and to predict participants' interviewer-rated enthusiasm for naming and recruiting their network members at both the Athens and Odessa sites. These findings suggest that network-based interventions like TRIP which aim to reduce HIV transmission likely do not increase stigma-related risks to participants, and may even encourage increased social support among network members. However, the present study is limited by its associational design and by some variation in implementation by study site. Future research should directly assess contextual differences to improve understanding of the implications of site-level variation in stigma and support for the implementation of network-based interventions, given the finding that these constructs predict participants' recruitment of network members and engagement in the intervention, and thereby could limit network-based interventions' abilities to reach those most in need of HIV testing and care. [ABSTRACT FROM AUTHOR]

Given globalization and other social phenomena, controlling the spread of infectious diseases has become an imperative public health priority. A plethora of interventions that in theory can mitigate the spread of pathogens have been proposed and applied. Evaluating the effectiveness of such interventions is costly and in many circumstances unrealistic. Most important, the community effect (i.e. the ability of the intervention to minimize the spread of the pathogen from people who received the intervention to other community members) can rarely be evaluated. Here we propose a study design that can build and evaluate evidence in support of the community effect of an intervention. The approach exploits molecular evolutionary dynamics of pathogens in order to track new infections as having arisen from either a control or an intervention group. It enables us to evaluate whether an intervention reduces the number and length of new transmission chains in comparison with a control condition, and thus lets us estimate the relative decrease in new infections in the community due to the intervention. We provide as an example one working scenario of a way the approach can be applied with a simulation study and associated power calculations. [ABSTRACT FROM AUTHOR]

As part of a network study of HIV infection among people who inject drugs (PWID) and their contacts, we discovered a connected subcomponent of 29 uninfected PWID. In the context of a just-declining large epidemic outbreak, this raised a question: What explains the existence of large pockets of uninfected people? Possible explanations include “firewall effects” (Friedman et al., 2000; Dombrowski et al., 2017) wherein the only HIV+ people that the uninfected take risks with have low viral loads; “bottleneck effects” wherein few network paths into the pocket of non-infection exist; low levels of risk behavior; and an impending outbreak. We considered each of these. Participants provided information on their enhanced sexual and injection networks and assisted us in recruiting network members. The largest connected component had 241 members. Data on risk behaviors in the last 6 months were collected at the individual level. Recent infection was determined by LAg (SediaTM Biosciences Corporation), data on recent seronegative tests, and viral load. HIV RNA was quantified using Artus HI Virus-1 RG RT-PCR (Qiagen). The 29 members of the connected subcomponent of uninfected participants were connected (network distance = 1) to 17 recently-infected and 24 long-term infected participants. Fourteen (48%) of these 29 uninfected were classified as “extremely high risk” because they self-reported syringe sharing and had at least one injection partner with viral load >100,000 copies/mL who also reported syringe sharing. Seventeen of the 29 uninfected were re-interviewed after 6 months, but none had seroconverted. These findings show the power of network research in discovering infection patterns that standard individual-level studies cannot. Theoretical development and exploratory network research studies may be needed to understand these findings and deepen our understanding of how HIV does and does not spread through communities. Finally, the methods developed here provide practical tools to study “bottleneck” and “firewall” network hypotheses in practice. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 PwRI) can reduce forward HIV transmission and help PwRI 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 PwRI 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 PwRI in an RDS‐based Integrated Biobehavioral Surveillance of people who inject drugs in 2013. Results: The networks of PwRI seeds and those of longer‐term infected seeds had similar (2%) proportions who were themselves PwRI. 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 PwRI 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 PwRI and reduce HIV transmission and should therefore be implemented. [ABSTRACT FROM AUTHOR]

Introduction: Viral load is one of the most important determinants for HIV transmission. Identification of people with high viral load (PHVL) can be effective in limiting onward HIV transmission. In order to improve the identification of these individuals within risk networks, we determined a) the number of PHVL recruited through risk networks b) their socio-demographic, behavioural and clinical characteristics and c) the characteristics of individuals who referred these PHVL to the study. Methodology: From November 2013 to March 2016, in Odessa, Ukraine, Transmission Reduction Intervention Project (TRIP) was implemented to identify people recently infected with HIV within the risk networks of "seeds" and "venues" where they engaged in risk behaviour. Results: TRIP identified 53 PHVL, of whom 32 (60%) injected drugs; 42 (79%) were unaware of their HIV status; 25 (47%) had more than one sex partner, and only 14 (26%) were using condoms. There were 164 people who referred individuals into the study; 33 of them (20%) referred PHVL. In terms of referrers, those with lower than secondary level of education, not living with a sex partner, and reporting regular condom use were significantly more likely (p < 0.05) to refer PHVL. Most PHVL (38, 72%) and their referrers (27, 82%) were found through venues. Conclusions: In Odessa city, PHVL are at high risk of transmitting HIV as the majority inject drugs, do not know their HIV status, and have unprotected sex and/or multiple partners. Targeting these individuals for HIV prevention, harm reduction and initiation of antiretroviral treatment (ART) is urgent. [ABSTRACT FROM AUTHOR]

Purpose: To assess cross-population linkages in HIV/AIDS epidemics, we tested the hypothesis that the number of newly diagnosed AIDS cases among Black people who inject drugs (PWID) was positively related to the natural log of the rate of newly diagnosed HIV infections among Black non-PWID heterosexuals in 84 large U.S. metropolitan statistical areas (MSAs) in 2008-2016.Methods: We estimated a multilevel model centering the time-varying continuous exposures at baseline between the independent (Black PWID AIDS rates) and dependent (HIV diagnoses rate among Black heterosexuals) variables.Results: At MSA level, baseline (standardized β = 0.12) Black PWID AIDS rates and change in these rates over time (standardized β = 0.11) were positively associated with the log of new HIV diagnoses rates among Black heterosexuals. Thus, MSAs with Black PWID AIDS rates that were 1 standard deviation= higher at baseline also had rates of newly diagnosed HIV infections among Black non-PWID heterosexuals that were 10.3% higher. A 1 standard deviation increase in independent variable over time corresponded to a 7.8% increase in dependent variable.Conclusions: Black PWID AIDS rates may predict HIV rates among non-PWID Black heterosexuals. Effective HIV programming may be predicated, in part, on addressing intertwining of HIV epidemics across populations. [ABSTRACT FROM AUTHOR]