A modeling framework to inform preexposure prophylaxis initiation and retention scale-up in the context of 'Getting to Zero' initiatives

"Make it more than a pill, make it an experience of health:" results from an open pilot intervention to retain young African American men who have sex with men in PrEP care

Uptake and retention in clinical care for pre-exposure prophylaxis (PrEP) is suboptimal, particularly among young African American men who have sex with men (MSM) in the Deep South. We conducted a two-phase study to develop and implement an intervention to increase PrEP persistence. In Phase I, we conducted focus groups with 27 young African American MSM taking PrEP at a community health center in Jackson, Mississippi to elicit recommendations for the PrEP persistence intervention. We developed an intervention based on recommendations in Phase I, and in Phase II, ten participants were enrolled in an open pilot. Eight participants completed Phase II study activities, including a single intervention session, phone call check-ins, and four assessments (Months 0, 1, 3, and 6). Exit interviews demonstrated a high level of acceptability and satisfaction with the intervention. These formative data demonstrate the initial promise of a novel intervention to improve PrEP persistence among young African American MSM.

Impact of post-incarceration care engagement interventions on HIV transmission among young Black men who have sex with men and their sexual partners: an agent-based network modeling study

Background

Understanding the impact of incarceration on HIV transmission among Black men who have sex with men is important given their disproportionate representation among people experiencing incarceration and the potential impact of incarceration on social and sexual networks, employment, housing, and medical care. We developed an agent-based network model (ABNM) of 10,000 agents representing young Black men who have sex with men in the city of Chicago to examine the impact of varying degrees of post-incarceration care disruption and care engagement interventions following release from jail on HIV incidence.

Methods

Exponential random graph models were used to model network formation and dissolution dynamics, and network dynamics and HIV care continuum engagement were varied according to incarceration status. Hypothetical interventions to improve post-release engagement in HIV care for individuals with incarceration (e.g., enhanced case management, linkage to housing and employment services) were compared to a control scenario with no change in HIV care engagement after release.

Finding

HIV incidence at 10 years was 4.98 [95% simulation interval (SI): 4.87, 5.09 per 100 person-years (py)] in the model population overall; 5.58 (95% SI 5.38, 5.76 per 100 py) among those with history of incarceration, and 12.86 (95% SI 11.89, 13.73 per 100 py) among partners of agents recently released from incarceration. Sustained post-release HIV care for agents with HIV and experiencing recent incarceration resulted in a 46% reduction in HIV incidence among post-incarceration partners [incidence rate (IR) per 100 py = 5.72 (95% SI 5.19, 6.27) vs. 10.61 (95% SI 10.09, 11.24); incidence rate ratio (IRR) = 0.54; (95% SI 0.48, 0.60)] and a 19% reduction in HIV incidence in the population overall [(IR per 100 py = 3.89 (95% SI 3.81-3.99) vs. 4.83 (95% SI 4.73, 4.92); IRR = 0.81 (95% SI 0.78, 0.83)] compared to a scenario with no change in HIV care engagement from pre-to post-release.

Interpretation

Developing effective and scalable interventions to increase HIV care engagement among individuals experiencing recent incarceration and their sexual partners is needed to reduce HIV transmission among Black men who have sex with men.

Funding

This work was supported by the following grants from the National Institutes of Health: R01DA039934; P20 GM 130414; P30 AI 042853; P30MH058107; T32 DA 043469; U2C DA050098 and the California HIV/AIDS Research Program: OS17-LA-003; H21PC3466.

Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas: Insights From a Modeling Study

CONTEXT

Medicaid expansion has been nationally shown to improve engagement in the human immunodeficiency virus (HIV) treatment and prevention continua, which are vital steps to stopping the HIV epidemic. New HIV infections in the United States are disproportionately concentrated among young Black men who have sex with men (YBMSM). Houston, TX, is the most populous city in the Southern United States with a racially/ethnically diverse population that is located in 1 of 11 US states that have not yet expanded Medicaid coverage as of 2021.

METHODS

An agent-based model that incorporated the sexual networks of YBMSM was used to simulate improved antiretroviral treatment and pre-exposure prophylaxis (PrEP) engagement through Medicaid expansion in Houston, TX. Analyses considered the HIV incidence (number of new infections and as a rate metric) among YBMSM over the next 10 years under Medicaid expansion as the primary outcome. Additional scenarios, involving viral suppression and PrEP uptake above the projected levels achieved under Medicaid expansion, were also simulated.

RESULTS

The baseline model projected an HIV incidence rate of 4.96 per 100 person years (py) and about 368 new annual HIV infections in the 10th year. Improved HIV treatment and prevention continua engagement under Medicaid expansion resulted in a 14.9% decline in the number of annual new HIV infections in the 10th year. Increasing viral suppression by an additional 15% and PrEP uptake by 30% resulted in a 44.0% decline in new HIV infections in the 10th year, and a 27.1% decline in cumulative infections across the 10 years of the simulated intervention.

FINDINGS

Simulation results indicate that Medicaid expansion has the potential to reduce HIV incidence among YBMSM in Houston. Achieving HIV elimination objectives, however, might require additional effective measures to increase antiretroviral treatment and PrEP uptake beyond the projected improvements under expanded Medicaid.

Characterizing the Impact of the COVID-19 Pandemic on HIV PrEP care: A Review and Synthesis of the Literature

The global COVID-19 pandemic and associated lockdown measures have caused disruptions to sexual health services and created additional barriers to the continuity of HIV pre-exposure prophylaxis (PrEP) among key populations. This review provides an examination of the influences of the pandemic on engagement in the PrEP care continuum. Using the PRISMA guideline, 46 studies were included in this review and the synthesis. Most of the studies were conducted in high-income settings through quantitative analysis. A majority of studies examining the changes in PrEP use suggested a decline or discontinuation in PrEP uptake during the pandemic. The most common reasons for stopping using PrEP were perceived barriers to PrEP-related care, having reduced sexual behaviors and fewer sexual partners, and reduced perceived risk of HIV infection. Limited studies documenting an increase in PrEP uptake were all in specific PrEP optimizing programs. During the pandemic, there is also an emerging trend of switching to on-demand PrEP from daily oral PrEP. Future studies should understand the mechanism of strategies that facilitated the improvements during the pandemic. PrEP implementation programs should consider alternative PrEP modalities and provide consistent and comprehensive knowledge about correct information.

DISTRIBUTED AGENT-BASED SIMULATION WITH REPAST4PY

The increasing availability of high-performance computing (HPC) has accelerated the potential for applying computational simulation to capture ever more granular features of large, complex systems. This tutorial presents Repast4Py, the newest member of the Repast Suite of agent-based modeling toolkits. Repast4Py is a Python agent-based modeling framework that provides the ability to build large, MPI-distributed agent-based models (ABM) that span multiple processing cores. Simplifying the process of constructing large-scale ABMs, Repast4Py is designed to provide an easier on-ramp for researchers from diverse scientific communities to apply distributed ABM methods. We will present key Repast4Py components and how they are combined to create distributed simulations of different types, building on three example models that implement seven common distributed ABM use cases. We seek to illustrate the relationship between model structure and performance considerations, providing guidance on how to leverage Repast4Py features to develop well designed and performant distributed ABMs.

Agent-based model projections for reducing HIV infection among MSM: Prevention and care pathways to end the HIV epidemic in Chicago, Illinois

Our objective is to improve local decision-making for strategies to end the HIV epidemic using the newly developed Levers of HIV agent-based model (ABM). Agent-based models use computer simulations that incorporate heterogeneity in individual behaviors and interactions, allow emergence of systemic behaviors, and extrapolate into the future. The Levers of HIV model (LHM) uses Chicago neighborhood demographics, data on sex-risk behaviors and sexual networks, and data on the prevention and care cascades, to model local dynamics. It models the impact of changes in local preexposure prophylaxis (PrEP) and antiretroviral treatment (ART) (ie, levers) for meeting Illinois' goal of "Getting to Zero" (GTZ) -reducing by 90% new HIV infections among men who have sex with men (MSM) by 2030. We simulate a 15-year period (2016-2030) for 2304 distinct scenarios based on 6 levers related to HIV treatment and prevention: (1) linkage to PrEP for those testing negative, (2) linkage to ART for those living with HIV, (3) adherence to PrEP, (4) viral suppression by means of ART, (5) PrEP retention, and (6) ART retention. Using tree-based methods, we identify the best scenarios at achieving a 90% HIV infection reduction by 2030. The optimal scenario consisted of the highest levels of ART retention and PrEP adherence, next to highest levels of PrEP retention, and moderate levels of PrEP linkage, achieved 90% reduction by 2030 in 58% of simulations. We used Bayesian posterior predictive distributions based on our simulated results to determine the likelihood of attaining 90% HIV infection reduction using the most recent Chicago Department of Public Health surveillance data and found that projections of the current rate of decline (2016-2019) would not achieve the 90% (p = 0.0006) reduction target for 2030. Our results suggest that increases are needed at all steps of the PrEP cascade, combined with increases in retention in HIV care, to approach 90% reduction in new HIV diagnoses by 2030. These findings show how simulation modeling with local data can guide policy makers to identify and invest in efficient care models to achieve long-term local goals of ending the HIV epidemic.

A Pilot Study of a Patient Navigation Intervention to Improve HIV Pre-exposure Prophylaxis Persistence Among Black/African American Men Who Have Sex With Men

BACKGROUND

Suboptimal HIV pre-exposure prophylaxis (PrEP) care outcomes among Black/African American men who have sex with men (MSM) limits its population-level effects on HIV incidence. We conducted a pilot study of a brief patient navigation intervention aimed at improving PrEP initiation and persistence among Black/African American MSM in the Southern United States.

SETTING

Community health center in Jackson, MS.

METHODS

We recruited 60 Black/African American MSM aged 18-34 years who were newly prescribed PrEP. Participants were randomized to receive the clinic's current standard of care or an intervention condition including a single patient navigation session to discuss and address perceived barriers to initiating and maintaining access to PrEP and biweekly check-ins. Participants were followed over 6 months using survey assessments, medical chart review, and pharmacy purchase records to ascertain PrEP initiation and persistence.

RESULTS

Participants in the intervention condition were more likely to pick up their initial PrEP prescription [RR: 1.47; 95% confidence interval (CI): 1.10 to 1.97], be retained in PrEP care at 3 months (RR: 1.62; 95% CI: 1.01 to 2.59) and 6 months (RR: 1.38; 95% CI: 0.64 to 2.93), and have access to PrEP medications greater than 80% of all study days based on pharmacy fill records (RR: 3.00; 95% CI: 1.50 to 5.98).

CONCLUSION

A brief patient navigation intervention demonstrated proof-of-concept in improving PrEP initiation and persistence among Black/African American MSM in the Southern United States.

Diagnosing PrEP Communication Self-Efficacy in a Community-Based Peer Leader Intervention for Black Sexual Minority Men

HIV prevention interventions that leverage endogenous peer leaders to communicate about Pre-Exposure Prophylaxis (PrEP) and other HIV prevention tools in their social networks offer a way to reach greater portions of communities most impacted by HIV like Black/African American gay, bisexual, same gender-loving, and other sexual minority men (BSMM). However, the success of these interventions hinge on the communication self-efficacy of its peer leaders. In this exploratory study, we present a multi-theoretical framework that situates the PrEP communication self-efficacy (PCSE) of a cohort of young BSMM peer leaders (n = 303) in the context of personal, behavioral, social, and structural factors. Using censored regression models, our analysis shows that PCSE is influenced by evaluations of PrEP itself (its relative advantage, complexity, and compatibility), network embeddedness (degree centrality) among other BSMM, social media network exposure to HIV information, and medical mistrust. We conclude with a discussion of the practical implications of our findings for intervention design and implementation.

Cost-Effectiveness of Interventions to Improve HIV Pre-exposure Prophylaxis Initiation, Adherence, and Persistence Among Men Who Have Sex With Men

BACKGROUND

To help achieve Ending the HIV Epidemic (EHE) goals of reducing new HIV incidence, pre-exposure prophylaxis (PrEP) use and engagement must increase despite multidimensional barriers to scale-up and limitations in funding. We investigated the cost-effectiveness of interventions spanning the PrEP continuum of care.

SETTING

Men who have sex with men in Atlanta, GA, a focal jurisdiction for the EHE plan.

METHODS

Using a network-based HIV transmission model, we simulated lifetime costs, quality-adjusted life years (QALYs), and infections averted for 8 intervention strategies using a health sector perspective. Strategies included a status quo (no interventions), 3 distinct interventions (targeting PrEP initiation, adherence, or persistence), and all possible intervention combinations. Cost-effectiveness was evaluated incrementally using a $100,000/QALY gained threshold. We performed sensitivity analyses on PrEP costs, intervention costs, and intervention coverage.

RESULTS

Strategies averted 0.2%-4.2% new infections and gained 0.0045%-0.24% QALYs compared with the status quo. Initiation strategies achieved 20%-23% PrEP coverage (up from 15% with no interventions) and moderate clinical benefits at a high cost, while adherence strategies were relatively low cost and low benefit. Under our assumptions, the adherence and initiation combination strategy was cost-effective ($86,927/QALY gained). Sensitivity analyses showed no strategies were cost-effective when intervention costs increased by 60% and the strategy combining all 3 interventions was cost-effective when PrEP costs decreased to $1000/month.

CONCLUSION

PrEP initiation interventions achieved moderate public health gains and could be cost-effective. However, substantial financial resources would be needed to improve the PrEP care continuum toward meeting EHE goals.

Stimulant use interventions may strengthen 'Getting to Zero' HIV elimination initiatives in Illinois: Insights from a modeling study

OBJECTIVE(S)

Getting to Zero (GTZ) is an Illinois-based HIV elimination initiative. GTZ identifies younger Black men who have sex with men (YBMSM) as a population who have experienced disproportionate HIV incidence. Rising stimulant use among YBMSM has been determined to impede engagement in the HIV prevention and treatment continua for reducing onward HIV transmission. Given the limited development of dedicated or culturally appropriate interventions for this population, this modeling study explores the impact of stimulant use on HIV incidence among YBMSM and assesses the impact of interventions to treat stimulant use on downstream HIV transmission to achieve GTZ goals.

METHODS

A previously developed agent-based network model (ABNM), calibrated using data for YBMSM in Illinois, was extended to incorporate the impact of stimulant use (methamphetamines, crack/cocaine, and ecstasy) on sexual networks and engagement in HIV treatment and prevention continua. The model simulated the impact of a residential behavioral intervention (BI) for reducing stimulant use and an outpatient biomedical intervention (mirtazapine) for treating methamphetamine use. The downstream impact of these interventions on population-level HIV incidence was the primary intervention outcome.

RESULTS

Baseline simulated annual HIV incidence in the ABNM was 6.93 [95% Uncertainty Interval (UI): 6.83,7.04] per 100 person years (py) and 453 [95% UI: 445.9,461.2] new infections annually. A residential rehabilitation intervention targeted to 25% of stimulant using persons yielded a 27.1% reduction in the annual number of new infections. Initiating about 50% of methamphetamine using persons on mirtazapine reduced the overall HIV incidence among YBMSM by about 11.2%. A 30% increase in antiretroviral treatment (ART) and preexposure prophylaxis (PrEP) uptake in the non-stimulant using YBMSM population combined with a 25% uptake of BI for stimulant using persons produces an HIV incidence consistent with HIV elimination targets (about 200 infections/year) identified in the GTZ initiative.

CONCLUSIONS

Behavioral and biomedical interventions to treat stimulant use, in addition to expanding overall ART and PrEP uptake, are likely to enhance progress towards achieving GTZ goals.

Population Impact and Efficiency of Improvements to HIV PrEP Under Conditions of High ART Coverage Among San Francisco Men Who Have Sex With Men

BACKGROUND

Key components of Ending the HIV Epidemic (EHE) plan include increasing HIV antiretroviral therapy (ART) and HIV pre-exposure prophylaxis (PrEP) coverage. One complication to addressing this service delivery challenge is the wide heterogeneity of HIV burden and health care access across the United States. It is unclear how the effectiveness and efficiency of expanded PrEP will depend on different baseline ART coverage.

METHODS

We used a network-based model of HIV transmission for men who have sex with men (MSM) in San Francisco. Model scenarios increased varying levels of PrEP coverage relative under current empirical levels of baseline ART coverage and 2 counterfactual levels. We assessed the effectiveness of PrEP with the cumulative percentage of infections averted (PIA) over the next decade and efficiency with the number of additional person-years needed to treat (NNT) by PrEP required to avert one HIV infection.

RESULTS

In our projections, only the highest levels of combined PrEP and ART coverage achieved the EHE goals. Increasing PrEP coverage up to 75% showed that PrEP effectiveness was higher at higher baseline ART coverage. Indeed, the PIA was 61% in the lowest baseline ART coverage population and 75% in the highest. The efficiency declined with increasing ART (NNT range from 41 to 113).

CONCLUSIONS

Improving both PrEP and ART coverage would have a synergistic impact on HIV prevention even in a high baseline coverage city such as San Francisco. Efforts should focus on narrowing the implementation gaps to achieve higher levels of PrEP retention and ART sustained viral suppression.

Novel population-level proxy measures for suboptimal HIV preexposure prophylaxis initiation and persistence in the USA

OBJECTIVE

In the United States (USA), HIV preexposure prophylaxis (PrEP) use is suboptimal. Population-level metrics on PrEP use are limited and focus on prescriptions issued rather than how much prescriptions are picked up. We introduce PrEP reversals, defined as when patients fail to pick up PrEP prescriptions at the pharmacy point-of-sale, as a proxy for PrEP initiation and persistence.

DESIGN

We analysed PrEP pharmacy claims and HIV diagnoses from a Symphony Health Solutions dataset across all US states from 1 October 2015 to 30 September 2019.

METHODS

We calculated the percentage of individuals who were newly prescribed PrEP and who reversed (i.e. patient did not pick up an insurance-approved prescription and pharmacy withdrew the claim), delayed (reversed and then picked up within 90 days), very delayed (reversed and then picked up between 90 and 365 days) or abandoned (not picked up within 365 days), and subsequent HIV diagnosis within 365 days.

RESULTS

Of 59 219 individuals newly prescribed PrEP, 19% reversed their index prescription. Among those, 21% delayed initiation and 8% had very delayed initiation. Seventy-one percent of patients who reversed their initial prescription abandoned it, 6% of whom were diagnosed with HIV---three times higher than those who persisted on PrEP.

CONCLUSION

Nearly one in five patients newlyprescribed PrEP reversed initial prescriptions, leading to delayed medication access, being lost to PrEP care, and dramatically higher HIV risk. Reversals could be used for real-time nationwide PrEP population-based initiation and persistence tracking, and for identifying patients that might otherwise be lost to care.

Iterative community-driven development of a SARS-CoV-2 tissue simulator

The 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable "choke points" for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.

Loss to Follow-Up and Re-Engagement in HIV Pre-Exposure Prophylaxis Care in the United States, 2013-2019

Retention in HIV pre-exposure prophylaxis (PrEP) care is critical for effective PrEP implementation. Few studies have reported long-term lost to follow-up (LTFU) and re-engagement in PrEP care in the United States. Medical record data for all cisgender patients presenting to the major Rhode Island PrEP clinic from 2013 to 2019 were included. LTFU was defined as no PrEP follow-up appointment within 98 days. Re-engagement in care was defined as individuals who were ever LTFU and later attended a follow-up appointment. Recurrent event survival analysis was performed to explore factors associated with PrEP retention over time. Of 654 PrEP patients, the median age was 31 years old [interquartile range (IQR): 25, 43]. The majority were male (96%), White (64%), non-Hispanic (82%), and insured (97%). Overall, 72% patients were ever LTFU and 27% of those ever LTFU re-engaged in care. Female patients were 1.37 times [crude hazard ratio (cHR): 1.37; 95% confidence interval (CI): 0.86-2.18] more likely to be LTFU than male patients, and a 1-year increase in age was associated with a 1% lower hazard of being LTFU (cHR: 0.99; CI: 0.98-0.99). Being either heterosexual (aHR: 2.25, 95% (CI): 1.70-2.99] or bisexual (aHR: 2.35, 95% CI: 1.15-4.82) was associated with a higher hazard of loss to follow-up compared with having same-sex partners only. The majority of PrEP users were LTFU, especially at the first 6 months of PrEP initiation. Although a significant number were re-engaged in care, targeted interventions are needed to improve retention in PrEP care. This study characterized the natural projection of loss to follow-up and re-engagement in HIV PrEP care using a longitudinal clinic cohort data and explored associated factors for guiding future interventions to improve retention in PrEP care.

Projecting the number of new HIV infections to formulate the "Getting to Zero" strategy in Illinois, USA

OBJECTIVES

Getting to Zero (GTZ) initiatives focus on expanding use of antiretroviral treatment (ART) and pre-exposure prophylaxis (PrEP) to eliminate new HIV infections. Computational models help inform policies for implementation of ART and PrEP continuums. Such models, however, vary in their design, and may yield inconsistent predictions. Using multiple approaches can help assess the consistency in results obtained from varied modeling frameworks, and can inform optimal implementation strategies.

METHODS

A study using three different modeling approaches is conducted. Two approaches use statistical time series analysis techniques that incorporate temporal HIV incidence data. A third approach uses stochastic stimulation, conducted using an agent-based network model (ABNM). All three approaches are used to project HIV incidence among a key population, young Black MSM (YBMSM), over the course of the GTZ implementation period (2016-2030).

RESULTS

All three approaches suggest that simultaneously increasing PrEP and ART uptake is likely to be more effective than increasing only one, but increasing ART and PrEP by 20% points may not eliminate new HIV infections among YBMSM. The results further suggest that a 20% increase in ART is likely to be more effective than a 20% increase in PrEP. All three methods consistently project that increasing ART and PrEP by 30% simultaneously can help reach GTZ goals.

CONCLUSIONS

Increasing PrEP and ART uptake by about 30% might be necessary to accomplish GTZ goals. Such scale-up may require addressing psychosocial and structural barriers to engagement in HIV and PrEP care continuums. ABNMs and other flexible modeling approaches can be extended to examine specific interventions that address these barriers and may provide important data to guide the successful intervention implementation.

Identifying influential neighbors in social networks and venue affiliations among young MSM: a data science approach to predict HIV infection

OBJECTIVE

Young MSM (YMSM) bear a disproportionate burden of HIV infection in the United States and their risks of acquiring HIV may be shaped by complex multilayer social networks. These networks are formed through not only direct contact with social/sex partners but also indirect anonymous contacts encountered when attending social venues. We introduced a new application of a state-of-the-art graph-based deep learning method to predict HIV infection that can identify influential neighbors within these multiple network contexts.

DESIGN AND METHODS

We used empirical network data among YMSM aged 16-29 years old collected from Houston and Chicago in the United States between 2014 and 2016. A computational framework GAT-HIV (Graph Attention Networks for HIV) was proposed to predict HIV infections by identifying influential neighbors within social networks. These networks were formed by multiple relations constituted of social/sex partners and shared venue attendances, and using individual-level variables. Further, GAT-HIV was extended to combine multiple social networks using multigraph GAT methods. A visualization tool was also developed to highlight influential network members for each individual within the multiple social networks.

RESULTS

The multigraph GAT-HIV models obtained average AUC values of 0.776 and 0.824 for Chicago and Houston, respectively, performing better than empirical predictive models (e.g. AUCs of random forest: 0.758 and 0.798). GAT-HIV on single networks also delivered promising prediction performances.

CONCLUSION

The proposed methods provide a comprehensive and interpretable framework for graph-based modeling that may inform effective HIV prevention intervention strategies among populations most vulnerable to HIV.

Partnership dynamics in mathematical models and implications for representation of sexually transmitted infections: a review

Mathematical models of sexually transmitted disease (STI) are increasingly relied on to inform policy, practice, and resource allocation. Because STI transmission requires sexual contact between two or more people, a model's ability to represent the dynamics of sexual partnerships can influence the validity of findings. This ability is to a large extent constrained by the model type, as different modeling frameworks vary in their capability to capture patterns of sexual contact at individual, partnership, and network levels. In this paper, we classify models into three groups: compartmental, individual-based, and statistical network models. For each framework, we describe the basic model structure and discuss key aspects of sexual partnership dynamics: how and with whom partnerships are formed, partnership duration and dissolution, and temporal overlap in partnerships (concurrency). We illustrate the potential implications of accurately accounting for partnership dynamics, but these effects depend on characteristics of both the population and pathogen; the combined impact of these partnership and epidemiologic dynamics can be difficult to predict. While each of the reviewed model frameworks may be appropriate to inform certain research or policy questions, modelers and consumers of models should carefully consider the implications of sexual partnership dynamics for the questions under study.

Added Benefits of Pre-Exposure Prophylaxis Use on HIV Incidence with Minimal Changes in Efficiency in the Context of High Treatment Engagement Among Men Who Have Sex with Men

Although there is ongoing debate over the need for substantial increases in pre-exposure prophylaxis (PrEP) use when antiretroviral treatment confers the dual benefits of reducing HIV-related morbidity and mortality and the risk of HIV transmission, no studies to date have quantified the potential added benefits of PrEP use and changes in its efficiency in the context of high treatment engagement across multiple US subpopulations. We used a previously published agent-based model to simulate HIV transmission in a dynamic network of Black/African American and White men who have sex with men (MSM) in Atlanta, Georgia (2015-2024) to understand how reductions in HIV incidence attributable to varying levels of PrEP use change when United Nations Joint Programme on HIV/AIDS (UNAIDS) "90-90-90" goals for HIV treatment are achieved and maintained. Even at achievement of "90-90-90" goals, 75% PrEP coverage further reduced incidence by 67.9% and 74.2% to 1.53 [simulation interval (SI): 1.39-1.70] and 0.355 (SI: 0.316-0.391) per 100 person-years for Black/African American and White MSM, respectively, compared with the same scenario with no PrEP use. Increasing PrEP coverage from 15% to 75% under "90-90-90" goals only increased the number of person-years of PrEP use per infection averted by 8.1% and 10.5% to 26.7 (SI: 25.6-28.0) and 73.3 (SI: 70.6-75.7) among Black/African American MSM and White MSM, respectively. Even with high treatment engagement, substantial expansion of PrEP use contributes to meaningful decreases in HIV incidence among MSM with minimal changes in efficiency.

Simulating the End of AIDS in New York: Using Participatory Dynamic Modeling to Improve Implementation of the Ending the Epidemic Initiative

OBJECTIVES

In 2014, the governor of New York announced the Ending the Epidemic (ETE) plan to reduce annual new HIV infections from 3000 to 750, achieve a first-ever decrease in HIV prevalence, and reduce AIDS progression by the end of 2020. The state health department undertook participatory simulation modeling to develop a baseline for comparing epidemic trends and feedback on ETE strategies.

METHODS

A dynamic compartmental model projected the individual and combined effects of 3 ETE initiatives: enhanced linkage to and retention in HIV treatment, increased preexposure prophylaxis (PrEP) among men who have sex with men, and expanded housing assistance. Data inputs for model calibration and low-, medium-, and high-implementation scenarios (stakeholders' rollout predictions, and lower and upper bounds) came from surveillance and program data through 2014, the literature, and expert judgment.

RESULTS

Without ETE (baseline scenario), new HIV infections would decline but remain >750, and HIV prevalence would continue to increase by 2020. Concurrently implementing the 3 programs would lower annual new HIV infections by 16.0%, 28.1%, and 45.7% compared with baseline in the low-, medium-, and high-implementation scenarios, respectively. In all concurrent implementation scenarios, although annual new HIV infections would remain >750, there would be fewer new HIV infections than deaths, yielding the first-ever decrease in HIV prevalence. PrEP and enhanced linkage and retention would confer the largest population-level changes.

CONCLUSIONS

New York State will achieve 1 ETE benchmark under the most realistic (medium) implementation scenario. Findings facilitated framing of ETE goals and underscored the need to prioritize men who have sex with men and maintain ETE's multipronged approach, including other programs not modeled here.

Projecting the impact of equity-based preexposure prophylaxis implementation on racial disparities in HIV incidence among MSM

BACKGROUND

It is unknown what levels of preexposure prophylaxis (PrEP) use are needed to reduce racial disparities in HIV incidence among men who have sex with men (MSM). Using an agent-based model, we quantified the impact of achieving PrEP coverage targets grounded in equity on racial disparities in HIV incidence among MSM in an urban setting in the Southeastern United States.

METHODS

An agent-based model was adapted to simulate HIV transmission in a network of Black/African American and White MSM aged 18-39 years in the Atlanta-Sandy Springs-Roswell metropolitan area over 10 years (2015-2024). Scenarios simulated coverage levels consistent with targets based on the ratio of the number of individuals using PrEP to the number of individuals newly diagnosed in a calendar year (i.e., the 'PrEP-to-need ratio'), ranging from 1 to 10. Incidence rate ratios and differences were calculated as measures of disparities.

RESULTS

Without PrEP, the model predicted a rate ratio of 3.82 and a rate difference of 4.50 comparing HIV incidence in Black/African American and White MSM, respectively. Decreases in the rate ratio of at least 50% and in the rate difference of at least 75% were observed in all scenarios in which the PrEP-to-need ratio among Black/African American MSM was 10, regardless of the value among White MSM.

CONCLUSION

Significant increases in PrEP use are needed among Black/African American MSM to reduce racial disparities in HIV incidence. PrEP expansion must be coupled with structural interventions to address vulnerability to HIV infection among Black/African American MSM.