Faculty Bibliography

We sought to disentangle effects of the components of a peer-education intervention on self-reported injection risk behaviors among people who inject drugs (n = 560) in Philadelphia, US. We examined 226 egocentric groups/networks randomized to receive (or not) the intervention. Peer-education training consisted of two components delivered to the intervention network index individual only: (1) an initial training and (2) "booster" training sessions during 6- and 12-month follow up visits. In this secondary data analysis, using inverse-probability-weighted log-binomial mixed effects models, we estimated the effects of the components of the network-level peer-education intervention upon subsequent risk behaviors. This included contrasting outcome rates if a participant is a network member [non-index] under the network exposure versus under the network control condition (i.e., spillover effects). We found that compared to control networks, among intervention networks, the overall rates of injection risk behaviors were lower in both those recently exposed (i.e., at the prior visit) to a booster (rate ratio [95% confidence interval]: 0.61 [0.46-0.82]) and those not recently exposed to it (0.81 [0.67-0.98]). Only the boosters had statistically significant spillover effects (e.g., 0.59 [0.41-0.86] for recent exposure). Thus, both intervention components reduced injection risk behaviors with evidence of spillover effects for the boosters. Spillover should be assessed for an intervention that has an observable behavioral measure. Efforts to fully understand the impact of peer education should include routine evaluation of spillover effects. To maximize impact, boosters can be provided along with strategies to recruit especially committed peer educators and to increase attendance at trainings. Clinical Trials Registration Clinicaltrials.gov NCT00038688 June 5, 2002.

Locating undiagnosed HIV infections is important for limiting transmission. However, there is limited evidence about how best to do so. In South Africa, men have been particularly challenging to reach for HIV testing due, in part, to stigma. We pilot-tested two versions of a network-based case-finding and care-linkage intervention. The first, TRIP, asked "seeds" (original participants) to recruit their sexual and/or injection partners. The second, TRIPLE, aimed to circumvent some stigma-related issues by asking seeds to recruit anyone they know who might be at risk of being HIV-positive-unaware. We recruited 11 (18% male) newly diagnosed HIV-positive (NDP) seeds from two clinics in KwaZulu-Natal, South Africa and randomly assigned them to either TRIP or TRIPLE. Network members were recruited two steps from each seed. The TRIP arm recruited 12 network members; the TRIPLE arm recruited 62. Both arms recruited NDPs at higher rates than local clinic testing, with TRIP (50.0%) outperforming (p = 0.012) TRIPLE (14.5%). However, TRIPLE (53.2%) was far superior to clinics (27.8%) and to TRIP (25.0%) at recruiting men. Given challenges around testing and treating men for HIV in this context, these findings suggest that the TRIPLE expanded network-tracing approach should be tested formally among larger samples in multiple settings.

Researchers across a wide array of disciplines are interested in finding the most influential subjects in a network. In a network setting, intervention effects and health outcomes can spill over from one node to another through network ties, and influential subjects are expected to have a greater impact than others. For this reason, network research in public health has attempted to maximize health and behavioral changes by intervening on a subset of influential subjects. Although influence is often defined only implicitly in most of the literature, the operative notion of influence is inherently causal in many cases: influential subjects are those we should intervene on to achieve the greatest overall effect across the entire network. In this work, we define a causal notion of influence using potential outcomes. We review existing influence measures, such as node centrality, that largely rely on the particular features of the network structure and/or on certain diffusion models that predict the pattern of information or diseases spreads through network ties. We provide simulation studies to demonstrate when popular centrality measures can agree with our causal measure of influence. As an illustrative example, we apply several popular centrality measures to the HIV risk network in the Transmission Reduction Intervention Project and demonstrate the assumptions under which each centrality can represent the causal influence of each participant in the study.

The Russian war in Ukraine poses many risks for the spread of HIV, TB and associated conditions, including possible increases in the numbers of people who inject drugs or engage in sex work in the years ahead. Ukrainian civil society and volunteer efforts have been able to maintain and at times expand services for HIV Key Populations. The extent of mutual-aid and volunteer efforts as well as the continued strength and vitality of harm reduction organizations such as the Alliance for Public Health and the rest of civil society will be crucial resources for postwar efforts to assist Key Populations and prevent the spread of HIV, TB and other diseases. The postwar period will pose great economic and political difficulties for Ukrainians, including large populations of people physically and/or psychically damaged and in pain who might become people who inject drugs. Local and international support for public health and for harm reduction will be needed to prevent potentially large-scale increases in infectious disease and related mortality.

Evaluating causal effects in the presence of interference is challenging in network-based studies of hard-to-reach populations. Like many such populations, people who inject drugs (PWID) are embedded in social networks and often exert influence on others in their network. In our setting, the study design is observational with a non-randomized network-based HIV prevention intervention. Information is available on each participant and their connections that confer possible HIV risk through injection and sexual behaviors. We considered two inverse probability weighted (IPW) estimators to quantify the population-level spillover effects of non-randomized interventions on subsequent health outcomes. We demonstrated that these two IPW estimators are consistent, asymptotically normal, and derived a closed-form estimator for the asymptotic variance, while allowing for overlapping interference sets (groups of individuals in which the interference is assumed possible). A simulation study was conducted to evaluate the finite-sample performance of the estimators. We analyzed data from the Transmission Reduction Intervention Project, which ascertained a network of PWID and their contacts in Athens, Greece, from 2013 to 2015. We evaluated the effects of community alerts on subsequent HIV risk behavior in this observed network, where the connections or links between participants were defined by using substances or having unprotected sex together. In the study, community alerts were distributed to inform people of recent HIV infections among individuals in close proximity in the observed network. The estimates of the risk differences for spillover using either IPW estimator demonstrated a protective effect. The results suggest that HIV risk behavior could be mitigated by exposure to a community alert when an increased risk of HIV is detected in the network.

The AIDS and COVID-19 pandemics demonstrated that nations at similar economic development levels varied widely in their capacity to protect the health of their residents. For AIDS, Britain and Australia brought gay representatives into official counsels and adopted harm reduction far more rapidly than the United States or Spain, and East African countries responded more effectively than South Africa or the Democratic Republic of the Congo. National responses to COVID-19 varied widely, with New Zealand, China, and Vietnam more effective than Italy, Brazil, or the United States. Further, as phylogenetic research has demonstrated, these pandemics spread from one country to another, with those that responded poorly acting as sources for mutations and potentially sources of transmission to countries with more effective responses. Many observers expressed surprise at the poor responses of the United States to COVID-19, but in retrospect the cutbacks in public health funding at state and national levels made it clear that this was a predictable weakness even in addition to the political vacillations that crippled the US and Brazilian responses. In a time of global sociopolitical and climate instability, it is important to measure and conduct research into spatial and time variations in 1. public health and medical funding, 2. social influence networks, social cohesion and trust, and stigmatization, 3. income inequality, 4. social conflict, and 5. other factors that affect responsiveness to pandemics.

IMPORTANCE:People who use drugs (PWUD) continue to be at risk of HIV infection, but the frequency and distribution of transmission-associated behaviors within various rural communities is poorly understood. OBJECTIVE:To examine the association of characteristics of rural PWUD with HIV transmission behaviors. DESIGN, SETTING, AND PARTICIPANTS:In this cross-sectional study, surveys of PWUD in rural communities in 10 states (Illinois, Kentucky, New Hampshire, Massachusetts, North Carolina, Ohio, Oregon, Vermont, West Virginia, and Wisconsin) were collected January 2018 through March 2020 and analyzed August through December 2022. A chain-referral sampling strategy identified convenience sample seeds who referred others who used drugs. Rural PWUD who reported any past 30-day injection drug use or noninjection opioid use "to get high" were included. EXPOSURES:Individual characteristics, including age, race, gender identity, sexual orientation, partnership status, drug of choice, and location, were collected. MAIN OUTCOMES AND MEASURES:Past 30-day frequency of behaviors associated with HIV transmission, including drug injection, syringe sharing, opposite- and same-gender partners, transactional sex, and condomless sex, was assessed. RESULTS:Of 3048 rural PWUD (mean [SD] age, 36.1 [10.3] years; 225 American Indian [7.4%], 96 Black [3.2%], and 2576 White [84.5%] among 3045 with responses; and 1737 men [57.0%] among 3046 with responses), most participants were heterosexual (1771 individuals [86.8%] among 2040 with responses) and single (1974 individuals [68.6%] among 2879 with responses). Opioids and stimulants were reported as drug of choice by 1636 individuals (53.9%) and 1258 individuals (41.5%), respectively, among 3033 individuals with responses. Most participants reported recent injection (2587 of 3046 individuals [84.9%] with responses) and condomless sex (1406 of 1757 individuals [80.0%] with responses), among whom 904 of 1391 individuals (65.0%) with responses indicated that it occurred with people who inject drugs. Syringe sharing (1016 of 2433 individuals [41.8%] with responses) and transactional sex (230 of 1799 individuals [12.8%] with responses) were reported less frequently. All characteristics and behaviors, except the number of men partners reported by women, varied significantly across locations (eg, mean [SD] age ranged from 34.5 [10.0] years in Wisconsin to 39.7 [11.0] years in Illinois; P < .001). In multivariable modeling, younger age (adjusted odds ratio [aOR] for ages 15-33 vs ≥34 years, 1.36; 95% CI, 1.08-1.72) and being single (aOR, 1.37; 95% CI, 1.08-1.74) were associated with recent injection; younger age (aOR, 1.49; 95% CI, 1.20-1.85) and bisexual orientation (aOR vs heterosexual orientation, 2.27; 95% CI, 1.60-3.23) with syringe sharing; gender identity as a woman (aOR vs gender identity as a man, 1.46; 95% CI, 1.01-2.12), bisexual orientation (aOR vs heterosexual orientation, 2.59; 95% CI, 1.67-4.03), and being single (aOR, 1.71; 95% CI, 1.15-2.55) with transactional sex; and bisexual orientation (aOR vs heterosexual orientation, 1.60; 95% CI, 1.04-2.46) and stimulants as the drug of choice (aOR vs opioids, 1.45; 95 CI, 1.09-1.93) with condomless sex with someone who injects drugs. CONCLUSIONS AND RELEVANCE:This study found that behaviors associated with HIV transmission were common and varied across communities. These findings suggest that interventions to reduce HIV risk among rural PWUD may need to be tailored to locally relevant factors.

BACKGROUND:Due to practical challenges associated with genetic sequencing in low-resource environments, the burden of hepatitis C virus (HCV) in forcibly displaced people is understudied. We examined the use of field applicable HCV sequencing methods and phylogenetic analysis to determine HCV transmission dynamics in internally displaced people who inject drugs (IDPWID) in Ukraine. METHODS:In this cross-sectional study, we used modified respondent-driven sampling to recruit IDPWID who were displaced to Odesa, Ukraine, before 2020. We generated partial and near full length genome (NFLG) HCV sequences using Oxford Nanopore Technology (ONT) MinION in a simulated field environment. Maximum likelihood and Bayesian methods were used to establish phylodynamic relationships. RESULTS:Between June and September 2020, we collected epidemiological data and whole blood samples from 164 IDPWID (PNAS Nexus.2023;2(3):pgad008). Rapid testing (Wondfo® One Step HCV; Wondfo® One Step HIV1/2) identified an anti-HCV seroprevalence of 67.7%, and 31.1% of participants tested positive for both anti-HCV and HIV. We generated 57 partial or NFLG HCV sequences and identified eight transmission clusters, of which at least two originated within a year and a half post-displacement. CONCLUSIONS:Locally generated genomic data and phylogenetic analysis in rapidly changing low-resource environments, such as those faced by forcibly displaced people, can help inform effective public health strategies. For example, evidence of HCV transmission clusters originating soon after displacement highlights the importance of implementing urgent preventive interventions in ongoing situations of forced displacement.

OBJECTIVE:The COVID-19 pandemic has significantly affected people's ability to buy, sell, and obtain items that they use in their daily lives. It may have had a particularly negative effect on the ability of people who use illicit opioids to obtain them because the networks they relied on are illicit and not part of the formal economy. Our objective in this research was to examine if, and how, disruptions related to COVID-19 of illicit opioid markets have affected people who use illicit opioids. METHOD:We collected 300 posts--including replies to posts--related to the intersection of COVID-19 and opioid use from Reddit.com, a forum that has several discussion threads (i.e., subreddits) dedicated to opioids. We then coded posts from the two most popular opioid subreddits during the early pandemic period (March 5, 2020-May 13, 2020) using an inductive/deductive approach. RESULTS:We found two themes related to active opioid use during the early pandemic: (a) changes in drug supply and difficulty obtaining opioids, and (b) buying less-trustworthy drugs from lesser-known sources. CONCLUSIONS:Our findings suggest that COVID-19 has created market conditions that place people who use opioids at risk of adverse outcomes, such as fatal overdose.