What do mathematical models tell us about the emergence and spread of drug-resistant HIV?
What do mathematical models tell us about the emergence and spread of drug-resistant HIV?
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DOI：
10.1097/coh.0b013e328343ad03
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发表时间：
2011-03-01
影响因子：
4.1
通讯作者：
Boily, Marie-Claude
中科院分区：
文献类型：
--
作者：
Baggaley, Rebecca F.;Powers, Kimberly A.;Boily, Marie-Claude
综述目的：探讨研究抗逆转录病毒（ARV）耐药性传播的最新HIV流行模型。最近的发现相对较少的传播模型研究了治疗性联合抗逆转录病毒治疗（cART）背景下的抗逆转录病毒耐药性；阴道杀菌剂（ARV-VMB）；以及口服暴露前预防（PrEP）。cART使用模型强调了对未来耐药性传播的潜在担忧，特别是在资源受限的环境中，并强调了病毒载量监测在限制耐药性传播方面的益处。PrEP模型得出的结论是，艾滋病毒感染者无意中使用PrEP可能会增加耐药性，而PrEP使用者的风险补偿可能会限制其对艾滋病毒传播的有益影响。ARV-VMB模型表明，尽管耐药性会降低女性ARV-VMB使用者预防艾滋病毒感染的预防效果，但如果女性使用者获得的耐药菌株的传播性低于野生型菌株，则可能同时使使用者的男性伴侣受益。这些模型在人口水平上检验了这两个因素之间的平衡。最近的艾滋病毒传播模型采用了各种各样的结构和假设，以探索不同环境下不同抗逆转录病毒药物干预措施下的耐药性。今后的工作需要强调多种抗逆转录病毒药物干预措施的同时效果，以及耐药性对公共卫生的影响，而不仅仅是其流行程度。
Purpose of reviewTo discuss recent HIV epidemic models examining the transmission of antiretroviral (ARV) drug resistance.Recent findingsA relatively small number of recent transmission models have investigated ARV resistance in the context of therapeutic, combined ART (cART); ARV-vaginal microbicides (ARV-VMB); and oral pre-exposure prophylaxis (PrEP). Models of cART use have highlighted potential concerns about future resistance transmission, particularly in resource-constrained settings, and have emphasized the benefits of viral load monitoring in limiting resistance spread. PrEP models have concluded that inadvertent use by HIV-infected individuals could increase resistance prevalence, and that risk compensation by PrEP users could limit their beneficial effects on HIV transmission. ARV-VMB models have demonstrated that whereas resistance can reduce prophylactic effectiveness in preventing HIV acquisition of female ARV-VMB users, it may concomitantly benefit users' male partners if the resistant strains that female users acquire are less transmissible than wild-type strains. The models have examined the balance between these two factors at the population level.SummaryRecent HIV transmission models have adopted a wide assortment of structures and assumptions to explore drug resistance in the context of different ARV interventions in various settings. There is a need for future work emphasizing the simultaneous effects of multiple ARV interventions, as well as the public health impact of resistance, not just its prevalence.