Modeling the Impact of Transcendental Meditation on Stroke Incidence and Mortality.

OBJECTIVES: Meditation has shown promise in clinical trials in reducing systolic blood pressure, one of the main risk factors for stroke. We aim to estimate the potential benefits of popularizing meditation on stroke incidence and mortality in the United States (U.S.). METHODS: We developed a dynamic population-based microsimulation model to simulate the disease progression of each individual and compute disease burden. We calibrated the microsimulation model for stroke incidence and further validated it by comparing the stroke-related mortality for each age group generated by the model with that observed in the U.S. We used the population simulation model to estimate the effects of meditation intervention on the number of stroke cases and deaths over a course of 15 years. RESULTS: Our results show that we could avert nearly 200,000 stroke cases and 50,000 stroke-related deaths over the course of 15 years. Our sensitivity analysis reveals that most of the benefits come from applying the intervention for individuals older than 60 years. In addition, meditation acceptance and adherence rate play a critical role in its effectiveness. CONCLUSIONS: The practice of meditation, if properly utilized along with the regular antihypertensive medication, could substantially alleviate the burden of stroke in the U.S. In order to design an effective meditation program, policymakers may prioritize funding to the programs that aim to encourage older individuals to practice meditation.

HIV Treatment in Resource-Limited Environments: Treatment Coverage and Insights.

BACKGROUND: The effects of antiretroviral treatment on the HIV epidemic are complex. HIV-infected individuals survive longer with treatment, but are less likely to transmit the disease. The standard coverage measure improves with the deaths of untreated individuals and does not consider the fact that some individuals may acquire the disease and die before receiving treatment, making it susceptible to overestimating the long-run performance of antiretroviral treatment programs. OBJECTIVE: The objective was to propose an alternative coverage definition to better measure the long-run performance of HIV treatment programs. METHODS: We introduced cumulative incidence-based coverage as an alternative to measure an HIV treatment program's success. To numerically compare the definitions, we extended a simulation model of HIV disease and treatment to represent a dynamic population that includes uninfected and HIV-infected individuals. Also, we estimated the additional resources required to implement various treatment policies in a resource-limited setting. RESULTS: In a synthetic population of 600,000 people of which 44,000 (7.6%) are infected, and eligible for treatment with a CD4 count of less than 500 cells/mm(3), assuming a World Health Organization (WHO)-defined coverage rate of 50% of eligible people, and treating these individuals with a single treatment regimen, the gap between the current WHO coverage definition and our proposed one is as much as 16% over a 10-year planning horizon. CONCLUSIONS: Cumulative incidence-based definition of coverage yields a more accurate representation of the long-run treatment success and along with the WHO and other definitions of coverage provides a better understanding of the HIV treatment progress.

Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model.

We developed a model to compare the impacts of different lifestyle interventions among prediabetes individuals and to identify the optimal age groups for such interventions. A stochastic simulation was developed to replicate the prediabetes and diabetes trends (1997-2010) in the U.S. adult population. We then simulated the population-wide impacts of three lifestyle diabetes prevention programs, i.e., the Diabetes Prevention Program (DPP), DPP-YMCA, and the Healthy Living Partnerships to Prevent Diabetes (HELP-PD), over a course of 10, 15 and 30 years. Our model replicated the temporal trends of diabetes in the U.S. adult population. Compared to no intervention, the diabetes incidence declined 0.3 per 1,000 by DPP, 0.2 by DPP-YMCA, and 0.4 by HELP-PD over the 15-year period. Our simulations identified HELP-PD as the most cost-effective intervention, which achieved the highest 10-year savings of $38 billion for those aged 25-65, assuming all eligible individuals participate in the intervention and considering intervention achievement rates. Our model simulates the diabetes trends in the U.S. population based on individual-level longitudinal data. However, it may be used to identify the optimal intervention for different subgroups in defined populations.

Efficient and Fair Heart Allocation Policies for Transplantation.

Background: The optimal allocation of limited donated hearts to patients on the waiting list is one of the top priorities in heart transplantation management. We developed a simulation model of the US waiting list for heart transplantation to investigate the potential impacts of allocation policies on several outcomes such as pre- and posttransplant mortality. Methods: We used data from the United Network for Organ Sharing (UNOS) and the Scientific Registry of Transplant Recipient (SRTR) to simulate the heart allocation system. The model is validated by comparing the outcomes of the simulation with historical data. We also adapted fairness schemes studied in welfare economics to provide a framework to assess the fairness of allocation policies for transplantation. We considered three allocation policies, each a modification to the current UNOS allocation policy, and analyzed their performance via simulation. The first policy broadens the geographical allocation zones, the second modifies the health status order for receiving hearts, and the third prioritizes patients according to their waiting time. Results: Our results showed that the allocation policy similar to the current UNOS practice except that it aggregates the three immediate geographical allocation zones, improves the health outcomes, and is "closer" to an optimal fair policy compared to all other policies considered in this study. Specifically, this policy could have saved 319 total deaths (out of 3738 deaths) during the 2006 to 2014 time horizon, in average. This policy slightly differs from the current UNOS allocation policy and allows for easy implementation. Conclusion: We developed a model to compare the outcomes of heart allocation policies. Combining the three immediate geographical zones in the current allocation algorithm could potentially reduce mortality rate and is closer to an optimal fair policy.

Measuring the Potential Impact of Combination HIV Prevention in Sub-Saharan Africa.

A public health approach to combination HIV prevention is advocated to contain the epidemic in sub-Saharan Africa. We explore the implications of universal access to treatment along with HIV education scale-up in the region. We develop an HIV transmission model to investigate the impacts of universal access to treatment, as well as an analytical framework to estimate the effects of HIV education scale-up on the epidemic. We calibrate the model with data from South Africa and simulate the impacts of universal access to treatment along with HIV education scale-up on prevalence, incidence, and HIV-related deaths over a course of 15 years. Our results show that the impact of combined interventions is significantly larger than the summation of individual intervention impacts (super-additive property). The combined strategy of universal access to treatment and HIV education scale-up decreases the incidence rate by 74% over the course of 15 years, whereas universal access to treatment and HIV education scale up will separately decrease that by 43% and 8%, respectively. Combination HIV prevention could be notably effective in transforming HIV epidemic to a low-level endemicity. Our results suggest that in designing effective combination prevention in sub-Saharan Africa, priorities should be given to achieving universal access to treatment as quickly as possible and improving compliance to condom use.

Should expectations about the rate of new antiretroviral drug development impact the timing of HIV treatment initiation and expectations about treatment benefits?

BACKGROUND: Many analyses of HIV treatment decisions assume a fixed formulary of HIV drugs. However, new drugs are approved nearly twice a year, and the rate of availability of new drugs may affect treatment decisions, particularly when to initiate antiretroviral therapy (ART). OBJECTIVES: To determine the impact of considering the availability of new drugs on the optimal initiation criteria for ART and outcomes in patients with HIV/AIDS. METHODS: We enhanced a previously described simulation model of the optimal time to initiate ART to incorporate the rate of availability of new antiviral drugs. We assumed that the future rate of availability of new drugs would be similar to the past rate of availability of new drugs, and we estimated the past rate by fitting a statistical model to actual HIV drug approval data from 1982-2010. We then tested whether or not the future availability of new drugs affected the model-predicted optimal time to initiate ART based on clinical outcomes, considering treatment initiation thresholds of 200, 350, and 500 cells/mm3. We also quantified the impact of the future availability of new drugs on life expectancy (LE) and quality-adjusted life expectancy (QALE). RESULTS: In base case analysis, considering the availability of new drugs raised the optimal starting CD4 threshold for most patients to 500 cells/mm3. The predicted gains in outcomes due to availability of pipeline drugs were generally small (less than 1%), but for young patients with a high viral load could add as much as a 4.9% (1.73 years) increase in LE and a 8% (2.43 QALY) increase in QALE, because these patients were particularly likely to exhaust currently available ART regimens before they died. In sensitivity analysis, increasing the rate of availability of new drugs did not substantially alter the results. Lowering the toxicity of future ART drugs had greater potential to increase benefit for many patient groups, increasing QALE by as much as 10%. CONCLUSIONS: The future availability of new ART drugs without lower toxicity raises optimal treatment initiation for most patients, and improves clinical outcomes, especially for younger patients with higher viral loads. Reductions in toxicity of future ART drugs could impact optimal treatment initiation and improve clinical outcomes for all HIV patients.

Evaluating the impact of prioritization of antiretroviral pre-exposure prophylaxis in New York.

OBJECTIVE: To compare the value and effectiveness of different prioritization strategies of pre-exposure prophylaxis (PrEP) in New York City (NYC). DESIGN: Mathematical modelling utilized as clinical trial is not feasible. METHODS: Using a model accounting for both sexual and parenteral transmission of HIV, we compare different PrEP prioritization strategies (PPS) with two scenarios ­ no PrEP and PrEP for all susceptible at-risk individuals. The PPS included PrEP for all MSM,only high-risk MSM, high-risk heterosexuals, and IDUs, and all combinations of these four strategies. Outcomes included HIV infections averted, and incremental cost effectiveness(per-infection averted) ratios. Initial assumptions regarding PrEP included a 44% reduction in HIV transmission, 50% uptake in the prioritized population and an annual cost per person of $9762. Sensitivity analyses on key parameters were conducted. RESULTS: Prioritization to all MSM results in a 19% reduction in new HIV infections. Compared with PrEP for all persons at-risk, this PPS retains 79% of the preventive effect at 15% of the total cost. PrEP prioritized to only high-risk MSM results in a reduction in new HIV infections of 15%. This PPS retains 60% of the preventive effect at 6% of the total cost. There are diminishing returns when PrEP utilization is expanded beyond this group. CONCLUSION: PrEP implementation is relatively cost-inefficient under our initial assumptions. Our results suggest that PrEP should first be promoted among MSM who are at particularly high risk of HIV acquisition. Further expansion beyond this group may be cost-effective, but is unlikely to be cost-saving.

Averting HIV infections in New York City: a modeling approach estimating the future impact of additional behavioral and biomedical HIV prevention strategies.

BACKGROUND: New York City (NYC) remains an epicenter of the HIV epidemic in the United States. Given the variety of evidence-based HIV prevention strategies available and the significant resources required to implement each of them, comparative studies are needed to identify how to maximize the number of HIV cases prevented most economically. METHODS: A new model of HIV disease transmission was developed integrating information from a previously validated micro-simulation HIV disease progression model. Specification and parameterization of the model and its inputs, including the intervention portfolio, intervention effects and costs were conducted through a collaborative process between the academic modeling team and the NYC Department of Health and Mental Hygiene. The model projects the impact of different prevention strategies, or portfolios of prevention strategies, on the HIV epidemic in NYC. RESULTS: Ten unique interventions were able to provide a prevention benefit at an annual program cost of less than $360,000, the threshold for consideration as a cost-saving intervention (because of offsets by future HIV treatment costs averted). An optimized portfolio of these specific interventions could result in up to a 34% reduction in new HIV infections over the next 20 years. The cost-per-infection averted of the portfolio was estimated to be $106,378; the total cost was in excess of $2 billion (over the 20 year period, or approximately $100 million per year, on average). The cost-savings of prevented infections was estimated at more than $5 billion (or approximately $250 million per year, on average). CONCLUSIONS: Optimal implementation of a portfolio of evidence-based interventions can have a substantial, favorable impact on the ongoing HIV epidemic in NYC and provide future cost-saving despite significant initial costs.