Improving HIV Early Infant Diagnosis Supply Chains in Sub-Saharan Africa: Models and Application to Mozambique
Improving HIV Early Infant Diagnosis Supply Chains in Sub-Saharan Africa: Models and Application to Mozambique
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DOI：
10.1287/opre.2017.1646
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发表时间：
2017-11-01
影响因子：
2.7
通讯作者：
Gallien, Jeremie
中科院分区：
文献类型：
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作者：
Jonasson, Jonas Oddur;Deo, Sarang;Gallien, Jeremie
对感染艾滋病毒的母亲所生婴儿进行人类免疫缺陷病毒（艾滋病毒）的早期诊断至关重要，因为大约50%未经治疗的感染婴儿在两岁之前死亡。然而，由于早期婴儿诊断（EID）网络的运营效率低下，撒哈拉以南非洲的大多数国家在诊断方面都出现了重大延误。我们开发了一个由两部分组成的建模框架，依靠优化和模拟来产生诊所到实验室的分配和实验室之间的能力分配的操作改进，并评估对婴儿开始治疗的数量的相关影响。将我们的方法应用于莫桑比克的EID计划数据，我们验证了我们的模拟模型，并估计最佳地将诊所重新分配给实验室将使平均样本周转时间（达特）减少11%，并使开始治疗的感染婴儿数量相对于当前系统增加约4%。此外，将所有诊断能力集中在一个集中的实验室将使平均TAT减少约22%，并使开始治疗的受感染婴儿数量增加7%。我们的敏感性分析表明，在一个单一的位置整合能力将保持接近最佳范围内的实验室利用水平在莫桑比克。然而，这种全面整合解决方案主要由两个或更多EID网络实验室的配置主导，平均运输时间比目前在莫桑比克观察到的至少长15%。
Early diagnosis of the human immunodeficiency virus (HIV) among infants born to HIV-infected mothers is critical because roughly 50% of untreated infected infants die before the age of two years. Yet most countries in sub-Saharan Africa experience significant delays in diagnosis because of operational inefficiencies in early infant diagnosis (EID) networks. We develop a two-part modeling framework relying on optimization and simulation to generate operational improvements in the assignment of clinics to laboratories and the allocation of capacity across laboratories, and to evaluate the associated impact on the number of infants initiating treatment. Applying our methodology to EID program data from Mozambique, we validate our simulation model and estimate that optimally reassigning clinics to labs would decrease the average sample turnaround time (TAT) by 11% and increase the number of infected infants starting treatment by about 4% relative to the current system. Furthermore, consolidating all diagnostic capacity in one centralized lab would decrease average TATs by an estimated 22% and increase the number of infected infants initiating treatment by 7%. Our sensitivity analysis suggests that the consolidation of capacity in a single location would remain near optimal across a wide range of laboratory utilization levels in Mozambique. However, this full consolidation solution is dominated by configurations with two or more labs for EID networks with average transportation times larger than those currently observed in Mozambique by at least 15%.