Of the estimated 1 million Americans who are currently infected with HIV, as many as 300,000 remain unaware of their infection and without access to life-prolonging care that could prevent further transmission. In 2002 and 2005, we were awarded funding to develop a computer-based evaluation model of the detection, clinical management, and economics of HIV disease. Our findings have had a profound impact on HIV screening policy and guideline development in the United States.
Our aims for this competing continuation are: 1. To refine the simulation model to more accurately portray the detection and risk of HIV infection, the natural history of early HIV disease, and the impact of screening on secondary HIV transmission. 2. To conduct a series of policy evaluations on questions arising from the CDC's 2006 revised recommendations for expanded HIV screening. We will: """""""" evaluate the CDC's proposed algorithms for HIV detection and confirmation in the US;"""""""" assess the cost-effectiveness of routine versus targeted strategies for HIV screening;"""""""" estimate the survival costs of inadequate HIV detection, linkage, and retention in the US;"""""""" forecast the budgetary impact of increased case identification and referral to care on the demand for publicly funded HIV services in the US (including Medicaid, the Ryan White CARE Act, and state AIDS Drug Assistance Programs). This proposal is motivated by several recent reports that identify inadequate HIV screening as a critical failing in the effort to contain the HIV epidemic in the US. This research plan will advance the state of the art in evidence-based, model-driven policy analysis.
Of the estimated 1 million Americans who are currently infected with HIV, roughly 300,000 remain unaware of their infection and without access to life-prolonging care that could prevent further transmission. This project uses a mathematical simulation model to assemble and analyze the best available clinical and cost data, to inform current policy debates, and to promote an evidence-based approach to HIV counseling, testing, and referral in the United States.
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