Faculty Bibliography

Despite the high incidence of HIV among young Black MSM in the United States and engagement in high risk behaviors, many men in this group avoid infection. This suggests that some men may engage in systematic risk reduction behaviors when not always using condoms or abstaining from substances. Using a "positive deviance" framework, we conducted qualitative interviews with HIV-negative, Black MSM between 25 and 35 who reported unprotected anal sex and drug use in the past six months or current heavy drinking (N = 29) to discover behaviors that could facilitate remaining HIV-uninfected. Findings showed that MSM who remain HIV negative despite continuing to engage in high-risk behaviors may be engaging in adaptive risk reduction behaviors that, through successive decisions and advance planning along the timeline to a sexual event, could lead to increased condom use, avoidance or delay of a risky sexual event, or reduction of HIV positive partners.

BACKGROUND:TRIP (Transmission Reduction Intervention Project) was a network-based, contact tracing approach to locate and link to care, mostly people who inject drugs (PWID) with recent HIV infection. OBJECTIVE:We investigated whether sequences from HIV-infected participants with high viral load cluster together more frequently than what is expected by chance. METHODS:Paired end reads were generated for 104 samples using Illumina MiSeq next-generation sequencing. RESULTS:63 sequences belonged to previously identified local transmission networks of PWID (LTNs) of an HIV outbreak in Athens, Greece. For two HIV-RNA cut-offs (105 and 106 IU/mL), HIV transmissions were more likely between PWID with similar levels of HIV-RNA (p<0.001). 10 of the 14 sequences (71.4%) from PWID with HIV-RNA >106 IU/mL were clustered in 5 pairs. For 4 of these clusters (80%), there was in each one of them at least one sequence from a recently HIVinfected PWID. CONCLUSION:We showed that transmissions are more likely among PWID with high viremia.

Background/UNASSIGNED:The Transmission Reduction Intervention Project (TRIP) is a network-based intervention that aims at decreasing human immunodeficiency virus type 1 (HIV-1) spread. We herein explore associations between transmission links as estimated by phylogenetic analyses, and social network-based ties among persons who inject drugs (PWID) recruited in TRIP. Methods/UNASSIGNED:Phylogenetic trees were inferred from HIV-1 sequences of TRIP participants. Highly supported phylogenetic clusters (transmission clusters) were those fulfilling 3 different phylogenetic confidence criteria. Social network-based ties (injecting or sexual partners, same venue engagement) were determined based on personal interviews, recruitment links, and field observation. Results/UNASSIGNED:TRIP recruited 356 individuals (90.2% PWID) including HIV-negative controls; recently HIV-infected seeds; long-term HIV-infected seeds; and their social network members. Of the 150 HIV-infected participants, 118 (78.7%) were phylogenetically analyzed. Phylogenetic analyses suggested the existence of 13 transmission clusters with 32 sequences. Seven of these clusters included 14 individuals (14/32 [43.8%]) who also had social ties with at least 1 member of their cluster. This proportion was significantly higher than what was expected by chance. Conclusions/UNASSIGNED: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.

PURPOSE:This paper presents an overview of different kinds of risk and social network methods and the kinds of research questions each can address. RECENT FINDINGS: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.

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.

BACKGROUND:Associations have been observed between an aggregate viral load measure, the community viral load, and new HIV diagnoses. The community viral load aggregates viral loads within chosen geographic areas, restricting inferences about HIV acquisition risk to these areas. We develop a more precise metric, the network viral load (NVL), to measure the composite viral load within a risk network of a HIV-negative individual. METHODS:We examined the relationship between NVL and HIV infection among young men who have sex with men in Chicago, United States. Networks were generated using respondent-driven sampling. NVL was defined as the prevalence of viremic individuals in one's risk network, characterized as those with a viral load ≥20 k copies per milliliter. Permutation tests were conducted to account for dependency. RESULTS:After controlling for total connections, age, substance use during sex, syphilis diagnosis (previous 12 months), and frequency of condomless anal sex (previous 6 months), we found a positive association between NVL and HIV infection. Compared with a network with all HIV-seronegative members, the odds of HIV infection with an NVL of <10% viremia were 1.85 (95% confidence interval: 1.18 to 2.92) times higher and those with an NVL of ≥10% viremia were 2.73 (95% confidence interval: 1.54 to 4.85) times higher. CONCLUSIONS:We found a positive association between NVL and HIV seroprevalence. Although limited in its ability to infer causality, NVL could have substantial public health implications for persons most at risk for HIV infection, given that this novel metric avoids overreliance on individual level behavior or broad community indices.

BACKGROUND:The United States has the highest incarceration rate in the world. Incarceration can increase HIV risk behaviors for individuals involved with the criminal justice system and may be a driver of HIV acquisition within the community. METHODS:We used an agent-based model to simulate HIV transmission in a sexual-contact network representing heterosexual African American men and women in Philadelphia to identify factors influencing the impact of male mass incarceration on HIV acquisition in women. The model was calibrated using surveillance data and assumed incarceration increased the number of sexual contacts and decreased HIV care engagement for men post-release. Incarceration of a partner increased the number of sexual contacts for women. We compared a counterfactual scenario with no incarceration to scenarios varying key parameters to determine what factors drove HIV acquisition in women. RESULTS:Setting the duration of male high-risk sexual behavior to two years post-release increased the number of HIV transmissions to women by more than 20%. Decreasing post-release HIV care engagement and increasing HIV acquisition risk attributable to sexually transmitted infections (STIs) also increased the number of HIV transmissions to women. Changing the duration of risk behavior for women, the proportion of women engaging in higher risk behavior, and the relative risk of incarceration for HIV-infected men had minimal impact. CONCLUSION/CONCLUSIONS:The mass incarceration of African American men can increase HIV acquisition in African American women on a population-level through factors including post-release high-risk behaviors, disruption of HIV care engagement among formerly incarcerated men, and increased STI prevalence. These findings suggest that the most influential points of intervention may be programs seeking to reduce male risk behaviors and promote HIV care engagement post-release, as well as STI testing and treatment programs for recently incarcerated men, as well as women with incarcerated partners.

Ukraine has one of the largest HIV epidemics in Europe, historically driven by people who inject drugs (PWID). The epidemic showed signs of stabilization in 2012, but the recent war in eastern Ukraine may be reigniting virus spread. We investigated the movement of HIV-infected people within Ukraine before and during the conflict. We analyzed HIV-1 subtype-A pol nucleotide sequences sampled during 2012-2015 from 427 patients of 24 regional AIDS centers and used phylogeographic analysis to reconstruct virus movement among different locations in Ukraine. We then tested for correlations between reported PWID behaviors and reconstructed patterns of virus spread. Our analyses suggest that Donetsk and Lugansk, two cities not controlled by the Ukrainian government in eastern Ukraine, were significant exporters of the virus to the rest of the country. Additional analyses showed that viral dissemination within the country changed after 2013. Spearman correlation analysis showed that incoming virus flow was correlated with the number of HIV-infected internally displaced people. Additionally, there was a correlation between more intensive virus movement and locations with a higher proportion of PWID practicing risky sexual behaviors. Our findings suggest that effective prevention responses should involve internally displaced people and people who frequently travel to war-affected regions. Scale-up of harm reduction services for PWID will be an important factor in preventing new local HIV outbreaks in Ukraine.

Implementation trials often involve clustering via risk networks, where only some participants directly receive the intervention. The individual effect is that among directly treated persons beyond being in an intervention network; the disseminated effect is that among persons engaged with those directly treated. In this article, we employ a causal inference framework and discuss assumptions and estimators for individual and disseminated effects and apply them to the HIV Prevention Trials Network 037 Study. HIV Prevention Trials Network 037 was a phase III, network-level, randomized controlled human immunodeficiency virus (HIV) prevention trial conducted in the United States and Thailand from 2002 to 2006 that recruited injection drug users, who were assigned to either an intervention group or a control group, and their risk network members, who received no direct intervention. Combining individual and disseminated effects, we observed a 35% composite rate reduction in the adjusted model (risk ratio = 0.65, 95% confidence interval: 0.47, 0.90). Methodology is now available for estimating the full set of these effects, enhancing knowledge gained from network-randomized trials. Although the overall effect gains validity from network randomization, we show that it will generally be less than the composite effect. Additionally, if only index participants benefit from the intervention, as the network size increases, the overall effect tends toward the null-an unfortunate and misleading conclusion.

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 (Sedia^TM 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.