The cost-effectiveness and population outcomes of expanded HIV screening and antiretroviral treatment in the United States

Progression and transmission of HIV (PATH 4.0)-A new agent-based evolving network simulation for modeling HIV transmission clusters

We present the Progression and Transmission of HIV (PATH 4.0), a simulation tool for analyses of cluster detection and intervention strategies. Molecular clusters are groups of HIV infections that are genetically similar, indicating rapid HIV transmission where HIV prevention resources are needed to improve health outcomes and prevent new infections. PATH 4.0 was constructed using a newly developed agent-based evolving network modeling (ABENM) technique and evolving contact network algorithm (ECNA) for generating scale-free networks. ABENM and ECNA were developed to facilitate simulation of transmission networks for low-prevalence diseases, such as HIV, which creates computational challenges for current network simulation techniques. Simulating transmission networks is essential for studying network dynamics, including clusters. We validated PATH 4.0 by comparing simulated projections of HIV diagnoses with estimates from the National HIV Surveillance System (NHSS) for 2010-2017. We also applied a cluster generation algorithm to PATH 4.0 to estimate cluster features, including the distribution of persons with diagnosed HIV infection by cluster status and size and the size distribution of clusters. Simulated features matched well with NHSS estimates, which used molecular methods to detect clusters among HIV nucleotide sequences of persons with HIV diagnosed during 2015-2017. Cluster detection and response is a component of the U.S. Ending the HIV Epidemic strategy. While surveillance is critical for detecting clusters, a model in conjunction with surveillance can allow us to refine cluster detection methods, understand factors associated with cluster growth, and assess interventions to inform effective response strategies. As surveillance data are only available for cases that are diagnosed and reported, a model is a critical tool to understand the true size of clusters and assess key questions, such as the relative contributions of clusters to onward transmissions. We believe PATH 4.0 is the first modeling tool available to assess cluster detection and response at the national-level and could help inform the national strategic plan.

Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review

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.

Costs of health resource utilization among HIV-positive individuals in British Columbia, Canada: results from a population-level study

BACKGROUND

Through delayed HIV disease progression, highly active antiretroviral therapy (HAART) may reduce direct medical costs, thus at least partially offsetting therapy costs. Recent findings regarding the secondary preventive benefits of HAART necessitate careful consideration of funding allocations for HIV/AIDS care. Our objective is to estimate non-HAART direct medical costs at different levels of disease progression and over time in British Columbia, Canada.

METHODS

We considered the population of individuals with HIV/AIDS within a set of linked disease registries and health administrative databases (N = 11,836) from 1996 to 2010. Costs of hospitalization, physician billing, diagnostic testing and non-HAART medications were calculated in 2010 Canadian dollars. Effects of covariates on quarterly costs were assessed with a two-part model with logit for probability of non-zero costs and a generalized linear model (GLM). Net effects of CD4 strata on direct non-HAART medical costs were evaluated over time during the study period.

RESULTS

Compared with person-quarters in which CD4 >500/mm(3), costs were Can$185 (95 % confidence interval [CI] 132-239) greater for CD4 350-500/mm(3), Can$441 (95 % CI 366-516) greater for CD4 200-350/mm(3) and Can$1,173 (95 % CI 1,051-1,294) greater when CD4 <200/mm(3). Prior to HIV care initiation, individuals incurred costs Can$385 (95 % CI 283-487) greater than in periods with CD4 >500/mm(3). Hospitalization comprised the majority of the increment in costs amongst those with no measured CD4. Evaluated at CD4 state conditional means, those with CD4 <200/mm(3) incurred quarterly costs of Can$5,781 (95 % CI 4,716-6,846) versus Can$1,307 (95 % CI 1,154-1,460; p < 0.001) for CD4 ≥500/mm(3) in 2010.

CONCLUSION

Non-HAART direct medical costs were substantially lower for individuals during periods of sustained virologic suppression and high CD4 count. HIV treatment and prevention evaluations require detailed health resource use data to inform funding allocation decisions.

The cost-effectiveness of preexposure prophylaxis for HIV prevention in the United States in men who have sex with men

BACKGROUND

A recent randomized, controlled trial showed that daily oral preexposure chemoprophylaxis (PrEP) was effective for HIV prevention in men who have sex with men (MSM). The Centers for Disease Control and Prevention recently provided interim guidance for PrEP in MSM at high risk for HIV. Previous studies did not reach a consistent estimate of its cost-effectiveness.

OBJECTIVE

To estimate the effectiveness and cost-effectiveness of PrEP in MSM in the United States.

DESIGN

Dynamic model of HIV transmission and progression combined with a detailed economic analysis.

DATA SOURCES

Published literature.

TARGET POPULATION

MSM aged 13 to 64 years in the United States.

TIME HORIZON

Lifetime.

PERSPECTIVE

Societal.

INTERVENTION

PrEP was evaluated in both the general MSM population and in high-risk MSM and was assumed to reduce infection risk by 44% on the basis of clinical trial results.

OUTCOME MEASURES

New HIV infections, discounted quality-adjusted life-years (QALYs) and costs, and incremental cost-effectiveness ratios.

RESULTS OF BASE-CASE ANALYSIS

Initiating PrEP in 20% of MSM in the United States would reduce new HIV infections by an estimated 13% and result in a gain of 550,166 QALYs over 20 years at a cost of $172,091 per QALY gained. Initiating PrEP in a larger proportion of MSM would prevent more infections but at an increasing cost per QALY gained (up to $216,480 if all MSM receive PrEP). Preexposure chemoprophylaxis in only high-risk MSM can improve cost-effectiveness. For MSM with an average of 5 partners per year, PrEP costs approximately $50,000 per QALY gained. Providing PrEP to all high-risk MSM for 20 years would cost $75 billion more in health care-related costs than the status quo and $600,000 per HIV infection prevented, compared with incremental costs of $95 billion and $2 million per infection prevented for 20% coverage of all MSM.

RESULTS OF SENSITIVITY ANALYSIS

PrEP in the general MSM population would cost less than $100,000 per QALY gained if the daily cost of antiretroviral drugs for PrEP was less than $15 or if PrEP efficacy was greater than 75%.

LIMITATION

When examining PrEP in high-risk MSM, the investigators did not model a mix of low- and high-risk MSM because of lack of data on mixing patterns.

CONCLUSION

PrEP in the general MSM population could prevent a substantial number of HIV infections, but it is expensive. Use in high-risk MSM compares favorably with other interventions that are considered cost-effective but could result in annual PrEP expenditures of more than $4 billion.

PRIMARY FUNDING SOURCE

National Institute on Drug Abuse, Department of Veterans Affairs, and National Institute of Allergy and Infectious Diseases.

Overview of screening: where we are and where we may be headed

This volume of Epidemiologic Reviews continues a discussion about screening within the evidence community that has been going on for many years. From various perspectives, the authors of these reviews consider the benefits and harms of screening for multiple conditions; the balance between benefits and harms (and costs) is often not clear. With few exceptions, the contribution of screening to improving the health of the public is small, yet it has become a popular and growing form of prevention. It may be that we are learning that the magnitude of benefit from screening is less than we hoped, and the harms may be greater than we thought. Perhaps we should not think of screening as our primary prevention strategy but rather use screening to make a real, but limited contribution to population health for a few conditions. We might target screening to smaller subpopulations with the highest potential benefit and the lowest potential harm. The payoff for population health could be greater if we shifted some resources we now devote to screening to developing, testing, and implementing alternative approaches to preventing the important threats to population health. There needs to be a wider discussion about these issues with the public.