Objective

The costs of medical care for people with HIV/AIDS (PWH) vary substantially across demographic groups, stages of disease progression and regionally across the United States. We aimed to estimate medical costs for PWH and examine the heterogeneity in costs within key patient groups typically distinguished in cost-effectiveness analyses.

Design

Retrospective cohort study using health administrative databases for diagnosed PWH in care at 17 HIV Research Network sites across the United States.

Methods

We estimated mean quarterly costs for key patient groups using multivariable generalized linear mixed effects models. We used quantile regression to highlight differences in the effect of covariates within each patient group (difference between covariate estimates at the mean versus the 90th percentile of quarterly costs), identifying covariates with a larger effect among the highest cost PWH, or generating greater uncertainty in mean cost estimates.

Results

Our sample included 40 022 patients with a median age of 39 years. Mean quarterly costs were highest for people who inject drugs with advanced disease progression and for PWH on antiretroviral treatment (ART). Within patient groups, we found the most heterogeneity at different levels of resource use for PWH on ART and PWH off ART with CD4 cell counts less than 200 cells/μl, people who inject drugs, as well as PWH in the South.

Conclusion

The study quantifies heterogeneity in costs both across and within key PWH patient groups. Our results highlight the need for sensitivity analysis on cost estimates and may inform decisions on model structure in cost-effectiveness analyses on HIV/AIDS treatment and prevention strategies.

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.

Aim

The aim was to estimate transitions between periods in and out of treatment, incarceration, and legal supervision, for prescription opioid (PO) and heroin users.

Methods

We captured all individuals admitted for the first time for publicly funded treatment for opioid use disorder (OUD) in California (2006 to 2010) with linked mortality and criminal justice data. We used Cox proportional hazards and competing risks models to assess the effect of primary PO use (v. heroin) on the hazard of transitioning among 5 states: (1) opioid detoxification treatment; (2) opioid agonist treatment (OAT); (3) legal supervision (probation or parole); (4) incarceration (jail or prison); and (5) out-of-treatment. Transitions were conditional on survival, and death was modeled as an absorbing state.

Results

Both primary PO (n = 11,733) and heroin (n = 19,926) users spent most of their median 2.3 y of observation out of treatment. Primary PO users were significantly younger (median age 30 v. 34 y), and a higher percentage were female (43.1% v. 31.5%; P < 0.001), white (74.6% v. 63.1%; P < 0.001), and had completed high school (31.8% v. 18.9%; P < 0.001). When compared to primary heroin users, PO users had a higher hazard of transitioning from detoxification to OAT (Hazard Ratio (HR), 1.65; 95% CI, 1.54 to 1.77), and had a lower hazard of transitioning from out-of-treatment to either detoxification (0.75 [0.70, 0.81]) or OAT (0.90 [0.85, 0.96]).

Conclusion

Our findings can be applied directly in state transition modeling to improve the validity of health economic evaluations. Although PO users tended to remain in treatment for longer durations than heroin users, they also tended to remain out of treatment for longer after transitioning to an out-of-treatment state. Despite the proven effectiveness of time-unlimited treatment, individuals with OUD spend most of their time out of treatment.

: 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.

Background

As countries embark on public health-oriented drug law reform, health impact evaluations are needed. In 2012, Mexico mandated the narcomenudeo reform, which depenalised the possession of small amounts of drugs and instituted drug treatment instead of incarceration. We investigated the past and future effect of this drug law reform on HIV incidence in people who inject drugs in Tijuana, Mexico.

Methods

In this epidemic modelling study, we used data from the El Cuete IV cohort study to develop a deterministic model of injecting and sexual HIV transmission in people who inject drugs in Tijuana between 2012 and 2030. The population was stratified by sex, incarceration status, syringe confiscation by the police, HIV stage, and exposure to drug treatment or rehabilitation (either opioid agonist treatment or compulsory drug abstinence programmes). We modelled the effect of these exposures on HIV risk in people who inject drugs, estimating the effect of observed and potential future reform enforcement levels.

Findings

In 2011, prior to the narcomenudeo reform, 547 (75%) of 733 people who inject drugs in the El Cuete cohort reported having ever been incarcerated, on average five times since starting injecting. Modelling estimated the limited reform implementation averted 2% (95% CI 0·2-3·0) of new HIV infections in people who inject drugs between 2012 and 2017. If implementation reduced incarceration in people who inject drugs by 80% from 2018 onward, 9% (95% CI 4-16) of new HIV infections between 2018 and 2030 could be averted, with 21% (10-33) averted if people who inject drugs were referred to opioid agonist treatment instead of being incarcerated. Referral to compulsory drug abstinence programmes instead of prison could have a lower or potentially negative impact with -2% (95% CI -23 to 9) infections averted.

Interpretation

Mexican drug law reform has had a negligible effect on the HIV epidemic among people who inject drugs in Tijuana. However, appropriate implementation could markedly reduce HIV incidence if linked to opioid agonist treatment. Unfortunately, compulsory drug abstinence programmes are the main type of drug rehabilitation available and their expansion could potentially increase HIV transmission.

Funding

National Institute on Drug Abuse, UC San Diego Center for AIDS Research.

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.