Background. Heterogeneity in HIV microepidemics across US cities necessitates locally oriented, combination implementation strategies to prioritize resources. We calibrated and validated a dynamic, compartmental HIV transmission model to establish a status quo treatment scenario, holding constant current levels of care for 6 US cities. Methods. Built off a comprehensive evidence synthesis, we adapted and extended a previously published model to replicate the transmission, progression, and clinical care for each microepidemic. We identified a common set of 17 calibration targets between 2012 and 2015 and used the Morris method to select the most influential parameters for calibration. We then applied the Nelder-Mead algorithm to iteratively calibrate the model to generate 2000 best-fitting parameter sets. Finally, model projections were internally validated with a series of robustness checks and externally validated against published estimates of HIV incidence, while the face validity of 25-year projections was assessed by a Scientific Advisory Committee (SAC). Results. We documented our process for model development, calibration, and validation to maximize its transparency and reproducibility. The projected outcomes demonstrated a good fit to calibration targets, with a mean goodness-of-fit ranging from 0.0174 (New York City [NYC]) to 0.0861 (Atlanta). Most of the incidence predictions were within the uncertainty range for 5 of the 6 cities (ranging from 21% [Miami] to 100% [NYC]), demonstrating good external validity. The face validity of the long-term projections was confirmed by our SAC, showing that the incidence would decrease or remain stable in Atlanta, Los Angeles, NYC, and Seattle while increasing in Baltimore and Miami. Discussion. This exercise provides a basis for assessing the incremental value of further investments in HIV combination implementation strategies tailored to urban HIV microepidemics.

Born out of a necessity for fiscal sustainability, simulation modeling is playing an increasingly prominent role in setting priorities for combination implementation strategies for HIV treatment and prevention globally. The design of a model and the data inputted into it are central factors in ensuring credible inferences. We executed a narrative review of a set of dynamic HIV transmission models to comprehensively synthesize and compare the structural design and the quality of evidence used to support each model. We included 19 models representing both generalized and concentrated epidemics, classified as compartmental, agent-based, individual-based microsimulation or hybrid in our review. We focused on four structural components (population construction; model entry, exit and HIV care engagement; HIV disease progression; and the force of HIV infection), and two analytical components (model calibration/validation; and health economic evaluation, including uncertainty analysis). While the models we reviewed focused on a variety of individual interventions and their combinations, their structural designs were relatively homogenous across three of the four focal components, with key structural elements influenced by model type and epidemiological context. In contrast, model entry, exit and HIV care engagement tended to differ most across models, with some health system interactions-particularly HIV testing-not modeled explicitly in many contexts. The quality of data used in the models and the transparency with which the data was presented differed substantially across model components. Representative and high-quality data on health service delivery were most commonly not accessed or were unavailable. The structure of an HIV model should ideally fit its epidemiological context and be able to capture all efficacious treatment and prevention services relevant to a robust combination implementation strategy. Developing standardized guidelines on evidence syntheses for health economic evaluation would improve transparency and help prioritize data collection to reduce decision uncertainty.

: Using a dynamic HIV transmission model calibrated for six USA cities, we projected HIV incidence from 2020 to 2040 and estimated whether an established UNAIDS HIV epidemic control target could be met under ideal implementation of optimal combination strategies previously defined for each city. Four of six cities (Atlanta, Baltimore, New York City and Seattle) were projected to achieve epidemic control by 2040 and we identified differences in reaching epidemic control across racial/ethnic groups.

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.

We estimated 10-year (2020-2030) trajectories for human immunodeficiency virus incidence in 6 US cities. Estimated incidence will only decrease in 2 of 6 cities, with the overall population-weighted incidence decreasing 3.1% (95% credible interval [CrI], -1.0% to 8.5%) by 2025, and 4.3% (95% CrI, -2.6% to 12.7%) by 2030 across cities. Targeted, context-specific combination implementation strategies will be necessary to meet the newly established national targets.

We estimated 10-year (2020-2030) trajectories for human immunodeficiency virus incidence in 6 US cities. Estimated incidence will only decrease in 2 of 6 cities, with the overall population-weighted incidence decreasing 3.1% (95% credible interval [CrI], -1.0% to 8.5%) by 2025, and 4.3% (95% CrI, -2.6% to 12.7%) by 2030 across cities. Targeted, context-specific combination implementation strategies will be necessary to meet the newly established national targets.

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.

We estimated human immunodeficiency virus incidence and incidence rate ratios (IRRs) for black and Hispanic vs white populations in 6 cities in the United States (2020-2030). Large reductions in incidence are possible, but without elimination of disparities in healthcare access, we found that wide disparities persisted for black compared with white populations in particular (lowest IRR, 1.69 [95% credible interval, 1.19-2.30]).

Background

Widespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities.

Methods

Using a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years.

Results

In the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city.

Conclusions

A campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.

Objective

Combination strategies generate health benefits through improved health outcomes among people living with HIV (PLHIV) and prevention of new infections. We aimed to determine health benefits attributable to improved health among PLHIV versus HIV prevention for a set of combination strategies in six US cities.

Design

A dynamic HIV transmission model.

Methods

Using a model calibrated for Atlanta, Baltimore, Los Angeles, Miami, New York City (NYC) and Seattle, we assessed the health benefits of city-specific optimal combinations of evidence-based interventions implemented at publicly documented levels and at ideal (90% coverage) scale-up (2020-2030 implementation, 20-year study period). We calculated the proportion of health benefit gains (measured as quality-adjusted life-years) resulting from averted and delayed HIV infections; improved health outcomes among PLHIV; and improved health outcomes due to medication for opioid use disorder (MOUD).

Results

The HIV-specific proportion of total benefits ranged from 68.3% (95% credible interval: 55.3-80.0) in Seattle to 98.5% (97.5-99.3) in Miami, with the rest attributable to MOUD. The majority of HIV-specific health benefits in five of six cities were attributable HIV prevention, and ranged from 33.1% (26.1-41.1) in NYC to 83.1% (79.6-86.6) in Atlanta. Scaling up to ideal service levels resulted in three to seven-fold increases in additional health benefits, mostly from MOUD, with HIV-specific health gains primarily driven by HIV prevention.

Conclusion

Optimal combination strategies generated a larger proportion of health benefits attributable to HIV prevention in five of six cities, underlining the substantial benefits of antiretroviral therapy engagement for the prevention of HIV transmission through viral suppression. Understanding to whom benefits accrue may be important in assessing the equity and impact of HIV investments.