Evidence map›Paper›PMID 42721131›Full record

ArticlePLOS global public health2026

Resources to implement general population mobile chest x-ray screening for tuberculosis in Uganda: A trial-based costing analysis.

Tyler Scott Johnson, David Isooba, Susan Birabwa, Juliet Kakeeto, Kenneth Ndyabayunga, Deborah Nantale, Ivan Mugabi, Violet Nakiiza, Annet Nalutaaya, Peter James Kitonsa and 3 more

Abstract read
In one paragraph

Article in PLOS global public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Tyler Scott JohnsonDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-0542-8300
David IsoobaUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.
Susan BirabwaUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.
Juliet KakeetoUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.ORCID https://orcid.org/0009-0001-8942-4816
Kenneth NdyabayungaUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.ORCID https://orcid.org/0009-0008-1782-3755
Deborah NantaleUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.
Ivan MugabiUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.
Violet NakiizaUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.
Annet NalutaayaUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.ORCID https://orcid.org/0000-0003-3903-303X
Peter James KitonsaUganda TB Implementation Research Consortium, Walimu, Kampala, Uganda.ORCID https://orcid.org/0000-0003-2971-216X
Emily A KendallDivision of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Achilles KatambaClinical Epidemiology and Biostatics Unit, Department of Internal Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
David W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0003-0481-7475

Funding

Hotspot versus clinic-based active case finding for TB in Uganda: A pragmatic randomized trialR01HL138728 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI David Wesley Dowdy, Emily A Kendall · 2017 to 2026
$5.4M
NHLBI NIH HHS R01 HL138728
6 · The paper itself

Abstract

Mobile chest X-ray (CXR) screening interventions are recommended for tuberculosis (TB) screening in high-burden settings, but implementation costs are variable and underreported. Using time-driven activity-based costing, we evaluated the costs of implementing general-population mobile CXR screening in peri-urban Uganda. We conducted a micro-costing analysis of mobile CXR screening using data from an ongoing randomized crossover trial. We adopted a healthcare payer perspective, categorizing costs into equipment, personnel, space, implementation, and consumables. We calculated per-participant costs for each step in the TB screening cascade, as well as total screening and diagnostic costs per positive microbiological result (Xpert Ultra). Sensitivity analyses evaluated the cost implications of varying the screening volume or radiographic risk score thresholds. Among 90,668 age-eligible participants completing CXR screening, 14,630 sputum specimens were collected for Xpert testing (16.1%), including 1,676 from participants who submitted sputum without completing CXR. Overall, 511 participants had valid Xpert-positive results (3.5%), corresponding to 5.6 Xpert-positive results per 1,000 CXRs performed. The estimated cost was $4.41 per person screened and $1,299 per Xpert-positive result (95% uncertainty interval: $1,134-$1,488). Screening and diagnostic costs accounted for 64% and 36% of the cost per Xpert-positive result, respectively. Daily screening volume strongly influenced the cost per positive Xpert result, whereas less stringent X-ray thresholds increased the number of TB cases detected with minimal impact on average cost per positive Xpert. Mobile CXR screening interventions for TB require substantial investment in resources. Program planners can optimize efficiency by targeting high-burden populations, increasing participant volume, and optimizing X-ray risk cutoffs for follow-up diagnostic testing. Our findings highlight the value of context-specific cost data for guiding decisions on scaling up TB screening interventions.

Identifiers

PMID42721131
PMCPMC13561341

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.