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Optimizing routine HIV viral load monitoring in pregnant and postpartum women

Optimizing routine HIV viral load monitoring in pregnant and postpartum women
优化孕妇和产后妇女的常规 HIV 病毒载量监测
批准号:
9751175
负责人:
Maia Rose Lesosky
金额:
$14.61万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-03-05 至 2021-01-31

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Project summary: There are more than 18 million HIV-infected (HIV+) women of childbearing age globally, and lifelong antiretroviral therapy (ART) is the critical intervention to support the long-term health of HIV+ women and mothers while reducing risks of sexual and mother-to-child transmission (MTCT). HIV Viral load (VL) monitoring is a critical tool to evaluate ART effectiveness and transmission risk and there is a global movement to expand use of VL monitoring. But while there are well-developed guidelines for implementing VL monitoring in non-pregnant adults on ART, there has been little consideration given to pregnant and postpartum women. There is a clear and urgent need for evidence-based recommendations into optimal VL monitoring strategies during pregnancy and the postpartum period. The overall goal of this study is to model the longitudinal VL trajectories of HIV+ women entering antenatal care, and then to use this simulation to determine optimal strategies for timing and frequency of VL monitoring in order to maximise the early detection of viraemia, reduce MTCT risk and minimize costs associated with non-informative VL testing. Specifically, the project will: develop a simulation model of longitudinal VL and associated MTCT risk during pregnancy and breastfeeding (Aim 1); determine the optimal VL monitoring strategies to detect elevated VL and minimise transmission risk (Aim 2); and evaluate how optimal VL monitoring strategies may be adapted to facilitate different interventions (such as enhanced infant antiretroviral prophylaxis for infants of mothers with elevated VL) and different programmatic settings (as the timing of ART initiation in pregnancy and levels of retention of women in ART services varies across countries, for instance). Throughout Aims 2 and 3, health systems costs and budget impact will be evaluated for different VL monitoring strategies. The research will provide the first model for determination of optimal VL monitoring schemes in pregnant and postpartum women and will provide critical information for health systems seeking to implement VL monitoring policies that recognise the special needs of this population, alongside the realities of routine chronic disease monitoring in resource-limited settings. In doing so the project will address the major gap in evidence-based recommendations for VL monitoring in this high-risk population and thus help inform the rapid scale-up of VL monitoring in sub-Saharan Africa.
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