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在GeneXpert上整合结核病和艾滋病毒检测可大幅改善检测可及性和实现同日诊断,使结核病防治项目受益:赞比亚的一项诊断网络优化分析

The integration of tuberculosis and HIV testing on GeneXpert can substantially improve access and same-day diagnosis and benefit tuberculosis programmes: A diagnostic network optimization analysis in Zambia.

作者信息

Girdwood Sarah, Pandey Mayank, Machila Trevor, Warrier Ranjit, Gautam Juhi, Mukumbwa-Mwenechanya Mpande, Benade Mariet, Nichols Kameko, Shibemba Lunda, Mwewa Joseph, Mzyece Judith, Lungu Patrick, Albert Heidi, Nichols Brooke, Choonga Powell

机构信息

Department of Internal Medicine, Health Economics and Epidemiology Research Office, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

Department of Medical Microbiology, Amsterdam University Medical Center, Amsterdam, The Netherlands.

出版信息

PLOS Glob Public Health. 2023 Jan 25;3(1):e0001179. doi: 10.1371/journal.pgph.0001179. eCollection 2023.

Abstract

Diagnostic network optimization (DNO), a geospatial optimization technique, can improve access to diagnostics and reduce costs through informing policy-makers' decisions on diagnostic network changes. In Zambia, viral load (VL) testing and early infant diagnosis (EID) for HIV has been performed at centralized laboratories, whilst the TB-programme utilizes a decentralized network of GeneXpert platforms. Recently, the World Health Organization (WHO) has recommended point-of-care (POC) EID/VL to increase timely diagnosis. This analysis modelled the impact of integrating EID/VL testing for children and pregnant/breastfeeding-women (priority-HIV) with TB on GeneXpert in Zambia. Using OptiDx, we established the baseline diagnostic network using inputs for testing demand (October 2019-September 2020), referrals, testing sites, testing platforms, and costs for HIV/TB testing (transport, test, device) respectively in Zambia. Next, we integrated priority-HIV testing on GeneXpert platforms, historically only utilized by the TB-programme. 228,265 TB tests were conducted on GeneXpert devices and 167,458 (99%) of priority-HIV tests on centralized devices at baseline, of which 10% were tested onsite at the site of sample collection. With integration, the average distance travelled by priority-HIV tests decreased 10-fold (98km to 10km) and the proportion tested onsite increased (10% to 48%). 52% of EID tests are likely to be processed within the same-day from a baseline of zero. There were also benefits to the TB-programme: the average distance travelled/specimen decreased (11km to 7km), alongside potential savings in GeneXpert device-operating costs (30%) through cost-sharing with the HIV-programme. The total cost of the combined testing programmes reduced marginally by 1% through integration/optimization. DNO can be used to strategically leverage existing capacity to achieve the WHO's recommendation regarding POC VL/EID testing. Through DNO of the Zambian network, we have shown that TB/HIV testing integration can improve the performance of the diagnostic network and increase the proportion of specimens tested closer to the patient whilst not increasing costs.

摘要

诊断网络优化(DNO)是一种地理空间优化技术,通过为政策制定者提供有关诊断网络变化的决策依据,可改善诊断服务的可及性并降低成本。在赞比亚,艾滋病毒的病毒载量(VL)检测和早期婴儿诊断(EID)在集中式实验室进行,而结核病项目则利用分散的GeneXpert平台网络。最近,世界卫生组织(WHO)建议采用即时检测(POC)进行EID/VL检测,以提高及时诊断率。本分析模拟了在赞比亚将儿童和孕妇/哺乳期妇女(优先艾滋病毒人群)的EID/VL检测与结核病检测整合到GeneXpert平台上的影响。我们使用OptiDx,分别根据赞比亚的检测需求(2019年10月至2020年9月)、转诊情况、检测地点、检测平台以及艾滋病毒/结核病检测成本(运输、检测、设备)等输入数据,建立了基线诊断网络。接下来,我们将优先艾滋病毒检测整合到GeneXpert平台上,该平台以往仅用于结核病项目。在基线时,在GeneXpert设备上进行了228,265次结核病检测,在集中式设备上进行了167,458次(99%)优先艾滋病毒检测,其中10%在样本采集地点进行现场检测。整合后,优先艾滋病毒检测的平均行程距离减少了10倍(从98公里降至10公里),现场检测的比例增加(从10%增至48%)。52%的EID检测可能在同一天内完成,而基线时这一比例为零。对结核病项目也有好处:每个样本的平均行程距离减少(从11公里降至7公里),同时通过与艾滋病毒项目分担成本,GeneXpert设备运营成本可能节省30%。通过整合/优化,联合检测项目的总成本略有降低,降幅为1%。DNO可用于战略性地利用现有能力,以实现世卫组织关于POC VL/EID检测的建议。通过对赞比亚网络进行DNO分析,我们表明结核病/艾滋病毒检测整合可提高诊断网络的性能,并增加在更接近患者的地方进行检测的样本比例,同时不会增加成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49ba/10022337/d743ae4ea189/pgph.0001179.g001.jpg

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PLoS One. 2021 Mar 9;16(3):e0248217. doi: 10.1371/journal.pone.0248217. eCollection 2021.
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