Evidence map›Paper›PMID 36963019›Full record

ArticlePLOS global public health2023

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.

Sarah Girdwood, Mayank Pandey, Trevor Machila, Ranjit Warrier, Juhi Gautam, Mpande Mukumbwa-Mwenechanya, Mariet Benade, Kameko Nichols, Lunda Shibemba, Joseph Mwewa and 5 more

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Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  13. Drug resistance profiles ofJAC-antimicrobial resistance · 2024
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  16. Transforming tuberculosis diagnosis.Nature microbiology · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Sarah GirdwoodDepartment of Internal Medicine, Health Economics and Epidemiology Research Office, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0002-8492-028X
Mayank PandeyFIND, Geneva, Switzerland.
Trevor MachilaCentre for Infectious Disease Research in Zambia, Lusaka, Zambia.ORCID https://orcid.org/0000-0002-1395-8221
Ranjit WarrierCentre for Infectious Disease Research in Zambia, Lusaka, Zambia.
Juhi GautamFIND, Geneva, Switzerland.
Mpande Mukumbwa-MwenechanyaCentre for Infectious Disease Research in Zambia, Lusaka, Zambia.ORCID https://orcid.org/0000-0002-4753-5075
Mariet BenadeDepartment of Global Health, Boston University School of Public Health, Boston, MA, United States of America.ORCID https://orcid.org/0000-0001-9498-3199
Kameko NicholsFIND, Geneva, Switzerland.ORCID https://orcid.org/0000-0002-6644-0725
Lunda ShibembaMinistry of Health, Lusaka, Zambia.
Joseph MwewaMinistry of Health, Lusaka, Zambia.
Judith MzyeceMinistry of Health, Lusaka, Zambia.
Patrick LunguNational TB and Leprosy Programme, Ministry of Health, Lusaka, Zambia.
Heidi AlbertFIND, Cape Town, South Africa.
Brooke NicholsDepartment of Internal Medicine, Health Economics and Epidemiology Research Office, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Powell ChoongaMinistry of Health, Lusaka, Zambia.ORCID https://orcid.org/0000-0002-6180-7460

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID36963019
PMCPMC10022337

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.