The impact of localized implementation: determining the cost-effectiveness of HIV prevention and care interventions across six United States cities

Abstract

Objective: Effective interventions to reduce the public health burden of HIV/AIDS can vary in their ability to deliver value at different levels of scale and in different epidemiological contexts. Our objective was to determine the cost-effectiveness of HIV treatment and prevention interventions implemented at previously documented scales of delivery in six US cities with diverse HIV microepidemics. Design: Dynamic HIV transmission model-based cost-effectiveness analysis. Methods: We identified and estimated previously documented scale of delivery and costs for 16 evidence-based interventions from the US CDC's Compendium of Evidence-Based Interventions and Best Practices for HIV Prevention. Using a model calibrated for Atlanta, Baltimore, Los Angeles, Miami, New York City and Seattle, we estimated averted HIV infections, quality-adjusted life years (QALY) gained and incremental cost-effectiveness ratios (healthcare perspective; 3% discount rate, 2018$US), for each intervention and city (10-year implementation) compared with the status quo over a 20-year time horizon. Results: Increased HIV testing was cost-saving or cost-effective across cities. Targeted preexposure prophylaxis for high-risk MSM was cost-saving in Miami and cost-effective in Atlanta ($6123/QALY), Baltimore ($18 333/QALY) and Los Angeles ($86 117/QALY). Interventions designed to improve antiretroviral therapy initiation provided greater value than other treatment engagement interventions. No single intervention was projected to reduce HIV incidence by more than 10.1% in any city. Conclusion: Combination implementation strategies should be tailored to local epidemiological contexts to provide the most value. Complementary strategies addressing factors hindering access to HIV care will be necessary to meet targets for HIV elimination in the United States.

Ending the HIV epidemic in the USA: an economic modelling study in six cities

“…In this economic modelling study, we used a computer simulation model based on our previous synthesis of the best available data on city-level HIV microepidemics 16 and evidence-based interventions to diagnose, treat, and prevent HIV. 10 We simulated HIV microepidemics in Atlanta (GA), Baltimore (MD), Los Angeles (CA), Miami (FL), New York City (NY), and Seattle (WA), capturing current availability of prevention, testing, and treatment services. 17 These cities were selected to show the breadth of differences in local demographics, structural features, and available services to address the HIV/AIDS epidemic in the USA.…”

“…Into our model, we incorporated 16 evidence-based interventions with established efficacy or effectiveness data and promising scalability according to three pillars of the ending the HIV epidemic strategy: protect (via HIV prevention programmes such as syringe service programmes, medication for opioid use disorder, and targeted PrEP); diagnose (via HIV testing); and treat (via ART initiation and retention and ART re-initiation; table 2). These interventions were selected from the US Centers for Disease Control and Prevention compendium of evidence-based interventions and best practices for HIV prevention and from the published literature, 10 Initially, we estimated ranges on the costs and level of scale-up according to publicly available evidence, 10 which constituted the previously documented level of implementation. We have documented our methods for estimating the effectiveness, scale, and costs of each individual intervention in a separate manuscript.…”

“…We have documented our methods for estimating the effectiveness, scale, and costs of each individual intervention in a separate manuscript. 10 Scaleup from existing service levels was implemented proportionally across risk and ethnic groups, implying an increased scale-up of delivery after implementation for groups receiving high service levels at baseline. Based on real-world evidence, the scenarios were designed to represent an estimate of the expected level of scale-up that can be achieved within current social and structural constraints on access to care.…”

“…53 We previously outlined limitations in the structure of the model, 18 the evidence base on which it was built, 16 and uncertainty in the previously documented scale-up of delivery and the attributable costs of implementation, delivery, and sustainment for each intervention. 10 We note that the status quo scenario should be considered a reflection of the expected trajectory of the HIV epidemic in each city, conditional on data available up to 2015. As we were unable to capture more recent advances in service delivery, we felt our status quo scenario represented the most objective course of action and the most relevant comparator for the interventions considered.…”

“…Furthermore, as a result of limitations at each stage of implementation, previously documented scale-ups of delivery of evidence-based interventions have been shown to have limited population effects. 10 A data-driven public health approach, embracing evidence-based interventions and engaging communities in ways that mitigate stigma and discrimination, has been proposed as a means of reaching the ambitious 2019 targets. 3,5 Focusing resources on those at greatest risk of infection and mortality has long been a central theme in guidance issued by the President's Emergency Fund for AIDS Research, WHO, and UNAIDS, with data-driven programming informed by a so-called know your epidemic assessment framework.…”