Epidemics of HIV in men who have sex with men (MSM) continue to expand in most countries. We sought to understand the epidemiological drivers of the global epidemic in MSM and why it continues unabated. We did a comprehensive review of available data for HIV prevalence, incidence, risk factors, and the molecular epidemiology of HIV in MSM from 2007 to 2011, and modelled the dynamics of HIV transmission with an agent-based simulation. Our findings show that the high probability of transmission per act through receptive anal intercourse has a central role in explaining the disproportionate disease burden in MSM. HIV can be transmitted through large MSM networks at great speed. Molecular epidemiological data show substantial clustering of HIV infections in MSM networks, and higher rates of dual-variant and multiple-variant HIV infection in MSM than in heterosexual people in the same populations. Prevention strategies that lower biological transmission and acquisition risks, such as approaches based on antiretrovirals, offer promise for controlling the expanding epidemic in MSM, but their potential effectiveness is limited by structural factors that contribute to low health-seeking behaviours in populations of MSM in many parts of the world.

In this article, we use newly developed statistical methods to examine the generative processes that give rise to widespread patterns in friendship networks. The methods incorporate both traditional demographic measures on individuals (age, sex, and race) and network measures for structural processes operating on individual, dyadic, and triadic levels. We apply the methods to adolescent friendship networks in 59 U.S. schools from the National Longitudinal Survey of Adolescent Health (Add Health). We model friendship formation as a selection process constrained by individuals' sociality (propensity to make friends), selective mixing in dyads (friendships within race, grade, or sex categories are differentially likely relative to cross-category friendships), and closure in triads (a friend's friends are more likely to become friends), given local population composition. Blacks are generally the most cohesive racial category, although when whites are in the minority, they display stronger selective mixing than do blacks when blacks are in the minority. Hispanics exhibit disassortative selective mixing under certain circumstances; in other cases, they exhibit assortative mixing but lack the higher-order cohesion common in other groups. Grade levels are always highly cohesive, while females form triangles more than males. We conclude with a discussion of how network analysis may contribute to our understanding of sociodemographic structure and the processes that create it.

Men who have sex with men (MSM) have been substantially affected by HIV epidemics worldwide. Epidemics in MSM are re-emerging in many high-income countries and gaining greater recognition in many low-income and middle-income countries. Better HIV prevention strategies are urgently needed. Our review of HIV prevention strategies for MSM identified several important themes. At the beginning of the epidemic, stand-alone behavioural interventions mostly aimed to reduce unprotected anal intercourse, which, although somewhat efficacious, did not reduce HIV transmission. Biomedical prevention strategies reduce the incidence of HIV infection. Delivery of barrier and biomedical interventions with coordinated behavioural and structural strategies could optimise the effectiveness of prevention. Modelling suggests that, with sufficient coverage, available interventions are sufficient to avert at least a quarter of new HIV infections in MSM in diverse countries. Scale-up of HIV prevention programmes for MSM is difficult because of homophobia and bias, suboptimum access to HIV testing and care, and financial constraints.

In this work, we estimate the proportions of transmissions occurring in main vs. casual partnerships, and by the sexual role, infection stage, and testing and treatment history of the infected partner, for men who have sex with men (MSM) in the US and Peru. We use dynamic, stochastic models based in exponential random graph models (ERGMs), obtaining inputs from multiple large-scale MSM surveys. Parallel main partnership and casual sexual networks are simulated. Each man is characterized by age, race, circumcision status, sexual role behavior, and propensity for unprotected anal intercourse (UAI); his history is modeled from entry into the adult population, with potential transitions including HIV infection, detection, treatment, AIDS diagnosis, and death. We implemented two model variants differing in assumptions about acute infectiousness, and assessed sensitivity to other key inputs. Our two models suggested that only 4–5% (Model 1) or 22–29% (Model 2) of HIV transmission results from contacts with acute-stage partners; the plurality (80–81% and 49%, respectively) stem from chronic-stage partners and the remainder (14–16% and 27–35%, respectively) from AIDS-stage partners. Similar proportions of infections stem from partners whose infection is undiagnosed (24–31%), diagnosed but untreated (36–46%), and currently being treated (30–36%). Roughly one-third of infections (32–39%) occur within main partnerships. Results by country were qualitatively similar, despite key behavioral differences; one exception was that transmission from the receptive to insertive partner appears more important in Peru (34%) than the US (21%). The broad balance in transmission contexts suggests that education about risk, careful assessment, pre-exposure prophylaxis, more frequent testing, earlier treatment, and risk-reduction, disclosure, and adherence counseling may all contribute substantially to reducing the HIV incidence among MSM in the US and Peru.

Recent advances in statistical network analysis based on the family of exponential random graph (ERG) models have greatly improved our ability to conduct inference on dependence in large social networks (Snijders 2002, Pattison and Robins 2002, Handcock 2002, Handcock 2003, Snijders et al. 2006, previous papers this issue). This paper applies advances in both model parameterizations and computational algorithms to an examination of the structure observed in an adolescent friendship network of 1,681 actors from the National Longitudinal Study of Adolescent Health (AddHealth). ERG models of social network structure are fit using the R package statnet, and their adequacy assessed through comparison of model predictions with the observed data for higher-order network statistics.For this friendship network, the commonly used model of Markov dependence leads to the problems of degeneracy discussed by Handcock (2002Handcock ( , 2003. On the other hand, model parameterizations introduced by Snijders et al (2006) and Hunter and Handcock (2006) avoid degeneracy and provide reasonable fit to the data. Degree-only models did a poor job of capturing observed network structure; those that did best included terms both for heterogeneous mixing on exogenous attributes (grade and self-reported race) as well as endogenous clustering. Networks simulated from this model were largely consistent with the observed network on multiple higher-order network statistics, including the number of triangles, the size of the largest component, the overall reachability, the distribution of geodesic distances, the degree distribution, and the shared partner distribution. The ability to fit such models to large datasets and to make inference about the underling processes generating the network represents a major advance in the field of statistical network analysis.The exponential random graph (ERG) class was first posited as an approach to model social network structure almost two decades ago (Frank and Strauss 1986), based upon work in spatial statistics (Besag 1974). The modeling class is extremely general, and as such should in theory be capable of capturing the structure of a wide array of empirical networks, allowing for statistical inference about that structure to be conducted. Nevertheless, most work in this field has focused on a small set of model specifications, most commonly the Markov graphs of Frank and Strauss (1986). Recent work has shown that these commonly used model specifications are in fact not well-suited to capturing the processes underlying many empirical networks, due to the problem of model degeneracy (Handcock 2002(Handcock , 2003. Degeneracy can be described in brief as the phenomenon in which a seemingly reasonable model can actually be such a bad mis-specification for an observed dataset as to render the observed data virtually impossible under the model. Instead, the social processes encapsulated by the model yield networks such as the full or empty graph, which are qualitatively dissimilar to the observed ...

The authors introduce basic concepts in SNA, along with methods for data collection, data processing, data analysis, and conduct analyses of a study relationship network. Also covered are generative processes that create observed study networks and practical issues, such as the unique aspects of human subjects review for network studies.

BackgroundAlthough many men who have sex with men (MSM) in Peru are unaware of their HIV status, they are frequent users of the Internet, and can be approached by that medium for promotion of HIV testing.MethodsWe conducted an online randomized controlled trial to compare the effect of HIV-testing motivational videos versus standard public health text, both offered through a gay website. The videos were customized for two audiences based on self-identification: either gay or non-gay men. The outcomes evaluated were ‘intention to get tested’ and ‘HIV testing at the clinic.’FindingsIn the non-gay identified group, 97 men were randomly assigned to the video-based intervention and 90 to the text-based intervention. Non-gay identified participants randomized to the video-based intervention were more likely to report their intention of getting tested for HIV within the next 30 days (62.5% vs. 15.4%, Relative Risk (RR): 2.77, 95% Confidence Interval (CI): 1.42–5.39). After a mean of 125.5 days of observation (range 42–209 days), 11 participants randomized to the video and none of the participants randomized to text attended our clinic requesting HIV testing (p = 0.001). In the gay-identified group, 142 men were randomized to the video-based intervention and 130 to the text-based intervention. Gay-identified participants randomized to the video were more likely to report intentions of getting an HIV test within 30 days, although not significantly (50% vs. 21.6%, RR: 1.54, 95% CI: 0.74–3.20). At the end of follow up, 8 participants who watched the video and 10 who read the text visited our clinic for HIV testing (Hazard Ratio: 1.07, 95% CI: 0.40–2.85).ConclusionThis study provides some evidence of the efficacy of a video-based online intervention in improving HIV testing among non-gay-identified MSM in Peru. This intervention may be adopted by institutions with websites oriented to motivate HIV testing among similar MSM populations.Trial registrationClinicaltrials.gov NCT00751192

This paper explores the roles of acute infection and concurrent partnerships in HIV transmission dynamics among young adults in Zimbabwe using realistic representations of the partnership network and all published estimates of stage-specific infectivity. We use dynamic exponential random graph models to estimate partnership network parameters from an empirical study of sexual behavior and drive a stochastic simulation of HIV transmission through this dynamic network. Our simulated networks match observed frequencies and durations of short-and longterm partnerships, with concurrency patterns specific to gender and partnership type. Our findings suggest that, at current behavior levels, the epidemic cannot be sustained in this population without both concurrency and acute infection; removing either brings transmission below the threshold for persistence. With both present, we estimate 20-25% of transmissions stem from acute-stage infections, 30-50% from chronic-stage, and 30-45% from AIDS-stage. The impact of acute infection is strongly moderated by concurrency. Reducing this impact by reducing concurrency could potentially end the current HIV epidemic in Zimbabwe.