Evidence map›Paper›PMID 40446169›Full record

ArticlePLOS global public health2025

Decentralized TB diagnostic testing with Truenat MTB Plus and MTB-RIF Dx vs. hub-and-spoke GeneXpert MTB/RIF Ultra in Mozambique and Tanzania: a cost and cost-effectiveness analysis.

Akash Malhotra, Délio Elísio, Antonio Machiana, Anange Lwilla, Jerry Hella, Neenah Young, Celso Khosa, Marta Cossa, Dinis Nguenha, Regino Mgaya and 13 more

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. 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

23 authors.

Akash MalhotraDepartment of Global Health, University of Washington, United States of America.ORCID https://orcid.org/0000-0002-9298-0936
Délio ElísioCentro de Investigação em Saúde de Manhiça, Mozambique.
Antonio MachianaInstituto Nacional de Saúde, Mozambique.
Anange LwillaMbeya Medical Research Center, National Institute for Medical Research, Tanzania.
Jerry HellaIfakara Health Institute, Tanzania.ORCID https://orcid.org/0000-0003-2392-8592
Neenah YoungDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, United States of America.ORCID https://orcid.org/0009-0005-6505-7088
Celso KhosaInstituto Nacional de Saúde, Mozambique.
Marta CossaCentro de Investigação em Saúde de Manhiça, Mozambique.
Dinis NguenhaCentro de Investigação em Saúde de Manhiça, Mozambique.
Regino MgayaMbeya Medical Research Center, National Institute for Medical Research, Tanzania.
Dionisia BalateInstituto Nacional de Saúde, Mozambique.ORCID https://orcid.org/0000-0002-6607-9554
Mikaela WatsonFIND, Geneva, Switzerland.ORCID https://orcid.org/0000-0001-7941-1643
Vinzeigh LeukesFIND, Geneva, Switzerland.
Lelisa FekaduDepartment of Global Health and Population, Harvard TH Chan School of Public Health, United States of America.
Saima BashirManchester Centre for Health Economics, University of Manchester, United Kingdom.
Adam Penn-NicholsonFIND, Geneva, Switzerland.
Morten RuhwaldFIND, Geneva, Switzerland.
Leyla LarssonDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Germany.
Monisha SharmaDepartment of Global Health, University of Washington, United States of America.ORCID https://orcid.org/0000-0002-7599-1561
Katharina KranzerDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Germany.
Claudia M DenkingerDepartment of Infectious Disease and Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Germany.ORCID https://orcid.org/0000-0002-7216-7067
David DowdyDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, United States of America.
T.B. CAPT consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In low-and middle-income countries, missed or delayed tuberculosis (TB) diagnoses contribute to avoidable morbidity, mortality, and transmission. Decentralized testing platforms, such as the Molbio Truenat, may offer solutions by providing accurate point-of-care testing, improving access, and lowering out-of-pocket costs. Despite these advantages, the overall cost and cost-effectiveness of identifying additional TB cases using the Truenat MTB assays remain inadequately explored and understood. We collected economic data from a multicentre randomized controlled trial of TB testing using decentralized Molbio Truenat platform with MTB Plus and MTB-RIF Dx assays (Truenat MTB assays) versus hub-and-spoke Xpert MTB/RIF Ultra (standard of care) in Tanzania and Mozambique (TB-CAPT Core trial). We estimated facility-based diagnostic cost per participant tested and incremental facility-based diagnostic cost per incremental participant initiating TB treatment within seven and sixty days from enrolment. We used the societal perspective and conducted sensitivity analyses to determine key drivers of cost-effectiveness. The facility-based diagnostic cost per participant initiating treatment within seven days from enrolment in Mozambique was $853(95% uncertainty range: $707, $1072) for hub-and-spoke testing and $690($588, $823) for decentralized testing; in Tanzania costs were $596($485, $746) for hub-and-spoke testing and $592($495, $715) for decentralized testing. At sixty days, costs per treatment initiation were $581($493, $706) for hub-and-spoke vs. $678($576, $811) for decentralized testing in Mozambique, and $391($324, $476) vs. $591($494, $716) in Tanzania. Comparing decentralized to hub-and-spoke testing, the incremental cost per incremental seven-day treatment initiation was $403(-$103, $941) in Mozambique and $580($167, $1638) in Tanzania, and $805(-$10107, $10560) and -$353(-$20299, $20802) for sixty-day treatment initiation, respectively. Utilization (i.e., testing volume) of decentralized equipment was the strongest driver of cost-effectiveness. Decentralized TB testing with Truenat MTB assays is cost-effective relative to hub-and-spoke testing in Mozambique and Tanzania.

Identifiers

PMID40446169
PMCPMC12124845

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Registered trials

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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.