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Simulation Modeling to Improve HIV/HCV Screening, Treatment and Care

Simulation Modeling to Improve HIV/HCV Screening, Treatment and Care
模拟建模改善 HIV/HCV 筛查、治疗和护理
批准号:
8846562
负责人:
Benjamin P. Linas
金额:
$61.24万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-06-15 至 2017-05-31

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DESCRIPTION (provided by applicant): HCV-related liver disease is a leading cause of mortality among HIV-infected individuals in the U.S. Current therapy for HCV infection has limited efficacy, but the first HCV protease inhibitors were recently approved by the FDA and have substantially improved treatment outcomes. Many HCV-infected individuals, however, are not aware that they are infected. Further, as a result of limited treatment uptake and high rates of loss to follow- up, few HIV/HCV co-infected patients ever initiate HCV therapy. Recognizing the public health challenge represented by HCV, the Institute of Medicine and American Association for the Study of Liver Diseases have called for studies to identify the best strategies for HCV screening and care delivery. We propose to build a mathematical model of HIV/HCV co-infection to generate urgently-needed evidence that will inform screening and treatment guidelines and improve patient outcomes. The three specific aims are: 1. To develop and validate a Monte Carlo simulation model of HIV/HCV co-infection that includes HCV and HIV screening, linkage to and retention in care, and treatment. 2. To use the model to conduct and disseminate a series of analyses that will develop the evidence needed to inform clinical guidelines for identifying and managing HIV/HCV co-infection in the era of directly acting antiviral therapies against HCV. 3. To conduct policy analyses that will develop priorities for improving access to HCV treatment and project the budgetary impact of widely-available directly acting therapies against HCV. The proposed specific aims will answer critical questions about the best strategies for identifying and treating HCV and HIV/HCV co-infection. The project will develop a durable platform poised to be the premier tool for rapidly conducting rigorous analyses of the comparative-effectiveness and cost-effectiveness of strategies for improving HCV and HIV/HCV care in the new era of effective HCV therapy.
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HEAL Data2Action Modeling and Economic Resource Center
HEAL Data2Action Modeling and Economic Resource Center
Researching Effective Strategies to Prevent Opioid Death (RESPOND)
  • 批准号:
    10804924
  • 项目类别:
  • 资助金额:
    $89.58万
  • 财政年份:
    2018
  • 负责人:
    Benjamin P. Linas
  • 依托单位:
Researching Effective Strategies to Prevent Opioid Death (RESPOND)
  • 批准号:
    10369647
  • 项目类别:
  • 资助金额:
    $68.65万
  • 财政年份:
    2018
  • 负责人:
    Benjamin P. Linas
  • 依托单位:
海外基金