HIV cluster detection and response (CDR) provides a framework for identifying rapid HIV transmission and guiding implementation of proven HIV prevention and care strategies. Characterizing the relative benefits of CDR is important for guiding policy makers in resource allocation for HIV prevention. We sought to understand how many HIV infections would need to be averted by CDR activities to achieve various return-on-investment (ROI) thresholds. We conducted an ROI analysis of CDR in 2022, incorporating costs and benefits across US jurisdictions funded for HIV surveillance and prevention. Setting ROI thresholds between 1 and 5, we estimated the number of HIV infections that would need to be averted annually by CDR activities to reach ROI thresholds. A scenario was considered cost saving if the ROI > 1. Based on the number of people in national priority molecular clusters and estimated transmission in these clusters, we determined the percent reduction in transmission within these clusters that would be required to achieve the threshold number of HIV infections averted. The number of HIV infections needing to be averted annually ranged from 19 infections (ROI = 1) to 94 infections (ROI = 5). Among 657 HIV transmissions within national priority molecular clusters, the percent reduction in HIV transmission needed to meet ROI thresholds ranged from 2.9% (ROI = 1) to 14.3% (ROI = 5). In conclusion, CDR activities would need to avert a minimal number of HIV infections nationally to achieve cost savings.

BACKGROUND: This manuscript describes an updated spreadsheet tool that sexually transmitted infection (STI) prevention programs in the United States can use to estimate the health and economic benefits of their STI and HIV prevention activities. METHODS: The development of the updated tool, STIC (Sexually Transmitted Infection Costs) Figure 2.0, involved two main components. First, we revised the tool to be more useful and user-friendly based on feedback from focus groups and usability testing. Second, we updated the mathematical model behind the calculations by (1) revising the model to reflect current STI and HIV prevention activities in the United States, (2) updating the epidemiological and economic parameters in the model using the best available evidence, and (3) including ranges (not just point estimates) in the model output. To demonstrate the use of STIC Figure 2.0, we applied it to estimate the impact of a hypothetical prevention program, consistent with that of a health department or large STI clinic in a metropolitan area. RESULTS: STIC Figure 2.0 incorporated new features, including an interactive user interface to explore findings and create customized charts for use in reports and presentations. The hypothetical example we analyzed illustrated how providing STI treatment to 2,680 people and HIV prevention services to 325 people could avert 1,253 adverse outcomes and save over $2 million in medical costs and productivity costs. CONCLUSIONS: Although subject to important limitations, STIC Figure 2.0 allows state and local programs, including STI clinics, to calculate evidence-based estimates of the impact of their program activities.

BACKGROUND: In 2019, there were an estimated 1.2 million persons with HIV (PWH) and 35,100 new infections in the United States. The HIV care continuum has a large influence on transmission dynamics. METHODS: We updated Progression and Transmission of HIV 3.0, an agent-based simulation model, to estimate 2019 HIV transmission rates and distribution of transmissions by the HIV care continuum, race/ethnicity, transmission group, and age group. RESULTS: In 2019, the estimated transmission rate in the United States was 2.94 new infections per 100 person-years (inf /100p-y). Transmission rates decreased along the HIV care continuum; the highest transmission rate was associated with persons with acute HIV infection and unaware of their HIV status at 16.35 inf /100p-y, followed by persons with HIV (non-acute) and unaware of their HIV status (9.52), persons aware of their HIV status and not in care (5.96), persons receiving HIV care (on antiretroviral therapy) but not virally suppressed (4.53), and persons virally suppressed (0). The highest transmission rate by transmission group was among men who have sex with men at 3.68 inf /100p-y. Transmission rates decreased as age increased and are similar by race/ethnicity, after accounting for the HIV care continuum. CONCLUSION: Our results support a continued emphasis on helping PWH move along the care continuum through early diagnosis, linkage to care, and adherence to ART, resulting in viral suppression to reduce HIV transmissions. Further, efforts should focus on reducing disparities in the provision of HIV prevention and care services, particularly for populations disproportionally affected by HIV.

BACKGROUND: Cost-effectiveness analysis of HIV self-testing using patient-level data from a randomized clinical trial can inform HIV prevention funding decisions. Cost-effectiveness analysis using net benefit regression addresses the sampling uncertainty in the trial data and the variability of policymakers' willingness to pay (WTP). METHODS: We used published data from a 12-month longitudinal randomized clinical trial that enrolled 2665 men who sex with men (MSM) randomly assigned to the self-testing arm (participants receiving self-test kits) and control arm (participants receiving standard-of-care), and the self-testing arm identified 48 additional new HIV cases. We used net benefit regression to investigate the cost-effectiveness of an HIV self-testing intervention, which compared the incremental cost per new HIV diagnosis with policymakers' WTP thresholds. We addressed the uncertainties in estimating the incremental cost and the policymakers' WTP per new diagnosis through the incremental net benefit (INB) regression and cost-effectiveness acceptability curve (CEAC) analyses. RESULTS: From the healthcare provider's perspective, the INB analysis showed a positive net-benefit of HIV self-testing compared to standard-of-care when policymakers' WTP per new HIV diagnosis was $9,365 (95% CI: $5,700 - $25,500) or higher. The CEAC showed that the probability of HIV self-testing being cost-effective compared to standard-of-care was 58% and >99% at a WTP of $10 000 and $50 000 per new HIV diagnosis, respectively. CONCLUSION: The INB and CEAC analyses suggest that HIV self-testing has the potential to be cost-effective for relatively low values of policymakers' WTP.

OBJECTIVE: Depression is prevalent among persons with HIV (PWH) and is associated with poorer adherence and lack of viral load suppression (VLS). When treated for depression, PWH are more likely to stay in HIV care and adhere to medications; however, for many PWH, depression is not adequately diagnosed or treated. We adapted Progression and Transmission of HIV (PATH 3.0), a U.S. agent-based dynamic stochastic simulation model, by incorporating a continuum of depression care and estimating the impact on VLS of an enhanced depression diagnosis and care scenario (EDC). METHODS: We compared EDC-whereby every PWH is assessed for depression, gets treatment if diagnosed, and of those, half achieve remission-to a status quo scenario (SQ) on VLS. Based on published findings, assumptions for SQ were: 34.7% depressed, 45% diagnosed, 55.3% treated and 33% of treated achieving remission. Compared to PWH without depression, we assumed the probability of being non-virally suppressed increased by 1.57 times for PWH with depression (PWH-D), and by 0.95 times for PWH with remitted depression. RESULTS: There was an average increase of 14.6% (11.5-18.5) in the proportion of PWH-D who achieved VLS in EDC compared to SQ. Among all PWH, there was a 4.7% (3.4-6.0) increase in the proportion who achieved VLS in EDC compared to SQ. CONCLUSIONS: Fully diagnosing and adequately treating depression would improve health and quality of life for a substantial proportion of PWH-D and result in a nearly 5% increase in expected rates of VLS in the United States, supporting national prevention goals.