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BackgroundDetection and management of acute HIV infection (AHI) is a clinical and public health priority, and HIV infections diagnosed among young adults aged 18 to 39 years are usually recent. Young adults with recent HIV acquisition frequently seek care for symptoms and could potentially be diagnosed through the health care system. Early recognition of HIV infection provides considerable individual and public health benefits, including linkage to treatment as prevention, access to risk reduction counseling and treatment, and notification of partners in need of HIV testing. ObjectiveThe Tambua Mapema Plus study aims to (1) test 1500 young adults (aged 18-39 years) identified by an AHI screening algorithm for acute and prevalent (ie, seropositive) HIV, linking all newly diagnosed HIV-infected patients to care and offering immediate treatment; (2) offer assisted HIV partner notification services to all patients with HIV, testing partners for acute and prevalent HIV infection and identifying local sexual networks; and (3) model the potential impact of these two interventions on the Kenyan HIV epidemic, estimating incremental costs per HIV infection averted, death averted, and disability-adjusted life year averted using data on study outcomes. MethodsA modified stepped-wedge design is evaluating the yield of this HIV testing intervention at 4 public and 2 private health facilities in coastal Kenya before and after intervention delivery. The intervention uses point-of-care HIV-1 RNA testing combined with standard rapid antibody tests to diagnose AHI and prevalent HIV among young adults presenting for care, employs HIV partner notification services to identify linked acute and prevalent infections, and follows all newly diagnosed patients and their partners for 12 months to ascertain clinical outcomes, including linkage to care, antiretroviral therapy (ART) initiation and virologic suppression in HIV-infected patients, and pre-exposure prophylaxis uptake in uninfected individuals in discordant partnerships. ResultsEnrollment started in December 2017. As of April 2020, 1374 participants have been enrolled in the observation period and 1500 participants have been enrolled in the intervention period, with 13 new diagnoses (0.95%) in the observation period and 37 new diagnoses (2.47%), including 2 AHI diagnoses, in the intervention period. Analysis is ongoing and will include adjusted comparisons of the odds of the following outcomes in the observation and intervention periods: being tested for HIV infection, newly diagnosed with prevalent or acute HIV infection, linked to care, and starting ART by week 6 following HIV diagnosis. Participants newly diagnosed with acute or prevalent HIV infection in the intervention period are being followed for outcomes, including viral suppression by month 6 and month 12 following ART initiation and partner testing outcomes. ConclusionsThe Tambua Mapema Plus study will provide foundational data on the potential of this novel combination HIV prevention intervention to reduce ongoing HIV transmission in Kenya and other high-prevalence African settings. Trial RegistrationClinicalTrials.gov NCT03508908; https://clinicaltrials.gov/ct2/show/NCT03508908 International Registered Report Identifier (IRRID)DERR1-10.2196/16198

BackgroundHIV testing is the gateway to HIV treatment and prevention. HIV self-testing (HIVST) has potential to increase testing; however, the potential population-level impact of HIVST on the HIV epidemic and the best strategies for promoting HIVST are unknown. Our aim is to inform public health approaches for promoting HIVST as part of a comprehensive strategy to reduce HIV incidence.MethodsStochastic network-based HIV transmission models were used to estimate how different HIVST strategies would affect HIV incidence in Seattle and Atlanta over 10 years. We included four types of HIV testers and implemented nine replacement and eleven supplementation strategies for HIVST.ResultsReplacement of clinic-based tests with HIVST increased HIV incidence in Seattle and Atlanta. The benefits of supplementary strategies depended on the tester type using HIVST. Targeting non-testers averted the highest number of cases per test. In Seattle 2.2 (95%SI=-77, 100.4) and 4.7 (95%SI=-35.7, 60.1) infections were averted per 1000 HIVST when non-testers used HIVST once or twice per year respectively. In Atlanta the comparable rates were 8.0 (95%SI=-60.3 to 77.7) and 6.7 (95%SI=-37.7, 41.0). Paradoxically, increasing testing among risk-based testers using HIVST increased incidence.ConclusionsThe population-level impact of HIVST depends on who is reached with HIVST, how kits are used, and by characteristics of the underlying epidemic and HIV care infrastructure. Targeted HIVST can be an effective component of a comprehensive HIV testing strategy. More work is needed to understand how to identify and target non-testers for self-testing implementation.

BackgroundHIV-1 set point viral load (SPVL) is a highly variable trait that influences disease progression and transmission risk. Men who are exclusively insertive (EI) during anal intercourse require more sexual contacts to become infected than exclusively receptive (ER) men. Thus, we hypothesize that EIs are more likely to acquire their viruses from highly infectious partners (i.e., with high SPVLs) and to have higher SPVLs than infected ERs.MethodsWe used a one-generation Bernoulli model, a dynamic network model, and data from the Multicenter AIDS Cohort Study (MACS) to examine whether and under what circumstances MSM differ in SPVL by sexual role.ResultsBoth models predicted higher SPVLs in EIs than role versatile (RV) or ER men, but only in scenarios where longer-term relationships predominated. ER and RV men displayed similar SPVLs. EI men remained far less likely than ER men to become infected, however. When the MACS data were limited by some estimates of lower sex partner counts (a proxy for longer relationships), EI men had higher SPVLs; these differences were clinically relevant (>0.3 log10 copies/mL) and statistically significant (p

Introduction: HIV pre-exposure prophylaxis (PrEP) is effective in preventing HIV transmission. United States Public Health Service (USPHS) clinical practice guidelines define biobehavioral indications for initiation. To assess guideline implementation, it is critical to quantify PrEP nonusers who are indicated and PrEP users who are not indicated. We sought to estimate current PrEP use among US men who have sex with men (MSM), characterize whether their PrEP use aligned with their current indications for PrEP, and assess whether the association between PrEP indications and PrEP use differed by demography or geography. Methods: Using data from a US web-based sexual network study of MSM between 2017 and 2019, we measured PrEP usage and assessed whether respondents met indications for PrEP. Log-binomial regression was used to estimate the relationship between PrEP indications and PrEP use, with adjustment for geography, age and race/ethnicity. Results: Of 3508 sexually active, HIV-negative MSM, 34% met indications for PrEP. The proportion with current PrEP use was 32% among MSM meeting indications and 11% among those without indications. Nearly 40% of those currently using PrEP did not meet indications for PrEP, and 68% of MSM with indications for PrEP were not currently using PrEP. After adjusting for geography and demographics, MSM with PrEP indications were about three times as likely to be currently using PrEP. This association varied slightly, but not significantly, by geographic region, age and race/ethnicity. Conclusions: Indications for PrEP strongly predicted current PrEP use among US MSM. However, we identified substantial misalignment between indications and use in both directions (indicated MSM who were not benefitting from PrEP, and MSM taking PrEP while not presently being indicated). PrEP underuse by those at greatest risk for HIV acquisition may limit the projected impact of PrEP implementation, despite reported increases in PrEP provision. This calls for further implementation efforts to improve PrEP delivery to those most in need during periods of elevated sexual risk and to close the gap between indications and uptake. Keywords: HIV; pre-exposure prophylaxis; prevention; men who have sex with men, 1 | INTRODUCTION Despite biomedical advances in human immunodeficiency virus (HIV) prevention with antiretroviral pre-exposure prophylaxis (PrEP), the burden of HIV among men who have sex with men (MSM) remains [...]

ObjectivesCombination packages for HIV prevention can leverage the effectiveness of biomedical and behavioural elements to lower disease incidence with realistic targets for individual and population risk reduction. We investigated how sexual network structures can maximise the effectiveness of a package targeting sexually active adults in sub-Saharan Africa (SSA) with intervention components for medical male circumcision (MMC) and sexual partnership concurrency (having >1 ongoing partner).MethodsNetwork-based mathematical models of HIV type 1 (HIV-1) transmission dynamics among heterosexual couples were used to explore how changes to MMC alone and in combination with changes to concurrency impacted endemic HIV-1 prevalence and incidence. Starting from a base model parameterised from empirical data from West Africa, we simulated the prevalence of circumcision from 10% to 90% and concurrency was modelled at four discrete levels corresponding to values observed across SSA.ResultsMMC and concurrency could contribute to the empirical variation in HIV-1 disease prevalence across SSA. Small reductions in concurrency resulted in large declines in HIV-1 prevalence. Scaling up circumcision in low-concurrency settings yields a greater relative benefit, but the absolute number of infections averted depends on both the circumcision coverage and baseline incidence. Epidemic extinction with this package will require substantial scale-up of MMC in low-concurrency settings.ConclusionsDynamic sexual network structure should be considered in the design and targeting of MMC within combination HIV-1 prevention packages. Realistic levels of coverage for these packages within southern Africa could lead to a reduction of incidence to the low levels observed in western Africa, and possibly, epidemic extinction.

BackgroundWe aim to identify optimal strategies for deploying pre-exposure prophylaxis among men who have sex with men (MSM) in the United States and Peru to maximize population-level effectiveness in an efficient manner. We use epidemic models to simulate the impact of targeting strategies. Most studies have focused on targeting either the general population or high-risk MSM. Alternative strategies, including serodiscordant couples, may better balance effectiveness and efficiency.MethodsWe use dynamic stochastic sexual network models based on exponential-family random graph modeling, parameterized from behavioral surveys of MSM in the United States and Peru. These models represent main partnerships and casual contacts separately, permitting modeling of interventions targeting men whose risk derives from combinations of relational types. We also model varying rates of uptake and adherence to pre-exposure prophylaxis (PrEP). We assess sensitivity of results to risk compensation through increases in condomless casual contacts and condomless sex in main partnerships.ResultsTargeting all men who are not exclusively insertive has the largest impact on HIV incidence, but targeting only those with high levels of casual activity yields comparable results using fewer person-years on PrEP. The effect is robust to risk compensation in the United States, but less so in Peru. Targeting serodiscordant main partnerships does not significantly impact incidence, but requires fewer person-years on PrEP per infection averted than other strategies.ConclusionsPrEP could be effective in reducing new infections at the population level in both settings. Serodiscordant partnerships are an attractive component of a targeting program, but targeting should include other high-risk men.

IntroductionPrevention of mother-to-child HIV transmission (PMTCT) strategies include combined short-course antiretrovirals during pregnancy (Option A), triple-drug antiretroviral treament (ART) during pregnancy and breastfeeding (Option B), or lifelong ART (Option B+). The WHO also recommends ART for HIV treatment and prevention of sexual transmission of HIV. The impact of PMTCT strategies on prevention of sexual HIV transmission of HIV is not known. We estimated the population-level impact of PMTCT interventions on heterosexual HIV transmission in southwestern Uganda and KwaZulu-Natal, South Africa, two regions with different HIV prevalence and fertility rates.Materials and methodsWe constructed and validated dynamic, stochastic, network-based HIV transmission models for each region. PMTCT Options A, B, and B+ were simulated over ten years under three scenarios: 1) current ART and PMTCT coverage, 2) current ART and high PMTCT coverage, and 3) high ART and PMTCT coverage. We compared adult HIV incidence after ten years of each intervention to Option A (and current ART) at current coverage.ResultsAt current coverage, Options B and B+ reduced heterosexual HIV incidence by about 5% and 15%, respectively, in both countries. With current ART and high PMTCT coverage, Option B+ reduced HIV incidence by 35% in Uganda and 19% in South Africa, while Option B had smaller, but meaningful, reductions. The greatest reductions in HIV incidence were achieved with high ART and PMTCT coverage. In this scenario, all PMTCT strategies yielded similar results.DiscussionImplementation of Options B/B+ reduces adult HIV incidence, with greater effect (relative to Option A at current levels) in Uganda than South Africa. These results are likely driven by Uganda's higher fertility rates.

PurposeIn this article, we examine the effectiveness of a variety of HIV diagnosis interventions in recently HIV-diagnosed men who have sex with men (MSM). These interventions use the preventive potential of postdiagnosis behavior change (PDBC), as measured by the reduction in the number of new infections. Empirical evidence for PDBC was presented in the behavioral substudy of the Southern California Acute Infection and Early Disease Research Program. In previous modeling work, we demonstrated the existing preventive effects of PDBC. However, a large proportion of new infections among MSM are either undiagnosed or diagnosed late, and the preventive potential of PDBC is not fully utilized.MethodsWe derive empirical, stochastic, network-based models to examine the effectiveness of several diagnosis interventions that account for PDBC among MSM over a 10-year period. These interventions involve tests with shorter detection windows, more frequent testing, and individualized testing regimens.ResultsWe find that individualized testing interventions (i.e., testing individuals every three partners or 3 months, whichever is first, or every six partners or 6 months, whichever is first) result in significantly fewer new HIV infections than the generalized interventions we consider.ConclusionsThis work highlights the potential of individualized interventions for new public health policies in HIV prevention.

Our objective here is to demonstrate the population-level effects of individual-level post-diagnosis behavior change (PDBC) in Southern Californian men who have sex with men (MSM), recently diagnosed with HIV. While PDBC has been empirically documented, the population-level effects of such behavior change are largely unknown. To examine these effects, we develop network models derived from the exponential random graph model family. We parameterize our models using behavioral data from the Southern California Acute Infection and Early Disease Research Program, and biological data from a number of published sources. Our models incorporate vital demographic processes, biology, treatment and behavior. We find that without PDBC, HIV prevalence among MSM would be significantly higher at any reasonable frequency of testing. We also demonstrate that higher levels of HIV risk behavior among HIV-positive men relative to HIV-negative men observed in some cross-sectional studies are consistent with individual-level PDBC.

Exponential-family random graph models (ERGMs) represent a powerful and flexible class of models for the statistical analysis of networks. statnet is a suite of software packages that implement these models. This paper details how the capabilities for ERGM modeling can be expanded and customized by programming additional network statistics that may be included in ERGMs. We describe a template R package called ergm.userterms that can be modified for this purpose. It is designed to make this process as straightforward as possible. We also explain some of the internal workings of statnet that will help users develop their own network analysis capabilities.

The statnet suite of R packages contains a wide range of functionality for the statistical analysis of social networks, including the implementation of exponential-family random graph (ERG) models. In this paper we illustrate some of the functionality of statnet through a tutorial analysis of a friendship network of 1,461 adolescents.

We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs): estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.

Temporal exponential-family random graph models (TERGMs) are a flexible class of models for network ties that change over time. Separable TERGMs (STERGMs) are a subclass of TERGMs in which the dynamics of tie formation and dissolution can be separated within each discrete time step and may depend on different factors. The Carnegie et al. approximation improves estimation efficiency for a subclass of STERGMs, allowing them to be reliably estimated from inexpensive cross-sectional study designs. This approximation adapts to cross-sectional data by attempting to construct a STERGM with two specific properties: a cross-sectional equilibrium distribution defined by an exponential-family random graph model (ERGM) for the network structure, and geometric tie duration distributions defined by constant hazards for tie dissolution. In this article we focus on approaches for improving the behavior of the Carnegie et al. approximation and increasing its scope of application. We begin with Carnegie et al.'s observation that the exact result is tractable when the ERGM is dyad-independent, and then show that taking the sparse limit of the exact result leads to a different approximation than the one they presented. We show that the new approximation outperforms theirs for sparse, dyad-independent models, and observe that the errors tend to increase with the strength of dependence for dyad-dependent models. We then develop theoretical results in the dyad-dependent case, showing that when the ERGM is allowed to have arbitrary dyad-dependent terms and some dyad-dependent constraints, both the old and new approximations are asymptotically exact as the size of the STERGM time step goes to zero. We note that the continuous-time limit of the discrete-time approximations has the desired cross-sectional equilibrium distribution and exponential tie duration distributions with the desired means. We show that our results extend to hypergraphs, and we propose an extension of the Carnegie et al. framework to dissolution hazards that depend on tie age. for this article are available online. [ABSTRACT FROM AUTHOR]