Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington, USA
National HIV Reference Laboratory, Kenya Ministry of Health, Nairobi, Kenya.
BMJ Open. 2024 Apr 3;14(4):e079988. doi: 10.1136/bmjopen-2023-079988.
HIV drug resistance (DR) is a growing threat to the durability of current and future HIV treatment success. DR testing (DRT) technologies are very expensive and specialised, relying on centralised laboratories in most low and middle-income countries. Modelling for laboratory network with point-of-care (POC) DRT assays to minimise turnaround time (TAT), is urgently needed to meet the growing demand.
We developed a model with user-friendly interface using integer programming and queueing theory to improve the DRT system in Kisumu County, Kenya. We estimated DRT demand based on both current and idealised scenarios and evaluated a centralised laboratory-only network and an optimised POC DRT network. A one-way sensitivity analysis of key user inputs was conducted.
In a centralised laboratory-only network, the mean TAT ranged from 8.52 to 8.55 working days, and the system could not handle a demand proportion exceeding 1.6%. In contrast, the mean TAT for POC DRT network ranged from 1.13 to 2.11 working days, with demand proportion up to 4.8%. Sensitivity analyses showed that expanding DRT hubs reduces mean TAT substantially while increasing the processing rate at national labs had minimal effect. For instance, doubling the current service rate at national labs reduced the mean TAT by only 0.0%-1.9% in various tested scenarios, whereas doubling the current service rate at DRT hubs reduced the mean TAT by 37.5%-49.8%. In addition, faster batching modes and transportation were important factors influencing the mean TAT.
Our model offers decision-makers an informed framework for improving the DRT system using POC in Kenya. POC DRT networks substantially reduce mean TAT and can handle a higher demand proportion than a centralised laboratory-only network, especially for children and pregnant women living with HIV, where there is an immediate push to use DRT results for patient case management.
艾滋病毒耐药性（DR）对当前和未来艾滋病毒治疗成功的持久性构成日益严重的威胁。耐药性检测（DRT）技术非常昂贵且专业化，大多数中低收入国家依赖于中央实验室。为了满足日益增长的需求，迫切需要建立一个实验室网络模型，使用即时检测（POC）DRT 检测来最小化周转时间（TAT）。
我们使用整数规划和排队论开发了一个具有用户友好界面的模型，以改善肯尼亚基苏木县的 DRT 系统。我们根据当前和理想的情况估计了 DRT 的需求，并评估了一个集中式实验室网络和一个优化的 POC DRT 网络。对关键用户输入进行了单向敏感性分析。
在集中式实验室网络中，平均 TAT 范围为 8.52 至 8.55 个工作日，系统无法处理超过 1.6%的需求比例。相比之下，POC DRT 网络的平均 TAT 范围为 1.13 至 2.11 个工作日，需求比例高达 4.8%。敏感性分析表明，扩大 DRT 中心可以大大缩短平均 TAT，同时增加国家实验室的处理率对 TAT 的影响最小。例如，在各种测试场景中，将国家实验室目前的服务率提高一倍仅将平均 TAT 降低 0.0%至 1.9%，而将 DRT 中心目前的服务率提高一倍将平均 TAT 降低 37.5%至 49.8%。此外，更快的批量处理模式和运输方式是影响平均 TAT 的重要因素。
我们的模型为决策者提供了一个框架，用于使用肯尼亚的即时检测来改进 DRT 系统。POC DRT 网络可大大缩短平均 TAT，并且可以处理比集中式实验室网络更高的需求比例，特别是对于儿童和艾滋病毒感染孕妇，他们立即需要使用 DRT 结果进行患者病例管理。
