Evidence map›Paper›PMID 42848772›Full record

ArticlePLOS global public health2026

Implementing computer‑aided detection for TB active case finding: A qualitative study of feasibility and acceptability in Tondo, Manila.

Emelie Yonally Phillips, Ma Danica Katrina P Galvan, Juno Min, Cathy Hewison, Carmina Duyala, John Carlo Palmado, Sheryl N Peral, Olivier Camelique, Mary Ruth C Roxas, Marve D Duka and 6 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

16 authors.

Emelie Yonally PhillipsEpicentre, Interventional Epidemiology and Training Department, Paris, France.ORCID https://orcid.org/0009-0000-7095-0851
Ma Danica Katrina P GalvanMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.
Juno MinMédecins Sans Frontières International, Amsterdam, Netherlands.ORCID https://orcid.org/0009-0003-9688-409X
Cathy HewisonMédecins Sans Frontières, Operational Center Paris, Paris, France.
Carmina DuyalaMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.
John Carlo PalmadoMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.
Sheryl N PeralMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.ORCID https://orcid.org/0009-0003-6067-6010
Olivier CameliqueMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.
Mary Ruth C RoxasMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.ORCID https://orcid.org/0009-0006-8906-4853
Marve D DukaMédecins Sans Frontières, Operational Center Paris, Tondo Project, Manila, Philippines.
Gina F PardillaResearch Office, Manila Health Department, Manila, Philippines.
Maria Julieta C RecidoroTB Prevention and Control Section, Manila Health Department, Manila, Philippines.
Richard H CastroTB Prevention and Control Section, Manila Health Department, Manila, Philippines.
Farah HossainMédecins Sans Frontières Operational Center Paris, Section Japan, Tokyo, Japan.
Helena HuergaEpicentre, Interventional Epidemiology and Training Department, Paris, France.ORCID https://orcid.org/0000-0003-0302-9063
Valentina CarnimeoEpicentre, Interventional Epidemiology and Training Department, Paris, France.ORCID https://orcid.org/0000-0001-5450-1255

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) remains the leading cause of death from a single infectious agent, with over 1.23 million deaths globally in 2024. Despite available treatment and prevention strategies, timely and accurate detection remains challenging, particularly in high-burden settings such as the Philippines, which accounted for 6.8% of the global burden of TB in 2024. Computer-aided detection (CAD) software integrated with digital chest X-ray offers enhanced screening capacity, but its success depends on feasibility and acceptability within local health systems. This qualitative study explored perceptions and experiences of CAD integration during a Médecins Sans Frontières community-based TB active case finding campaign (ACF) in Tondo, Manila. In-depth interviews, focus group discussions, and direct observations were conducted with MSF staff, health center physicians, TB program personnel, ACF participants, and community leaders between January and April 2023. Thematic analysis identified four main themes: (1) Operational functionality and efficiency: Staff reported CAD increased screening capacity, supported clinical decision-making, and streamlined workloads; ACF participants reported a convenient process. (2) Human resources and role adaptation: Staff perceived role redistribution as initially challenging, highlighting the need for adequate capacity building and technical support; (3) Technical feasibility and system design: project managers and staff emphasized understanding CAD's capabilities and limitations to plan infrastructure, set thresholds, and compensate for inherent limitations. (4) Community acceptability and ethical considerations: community participants expressed mixed views on the reliability of novel "high-tech" tools and stressed the importance of aligning with local healthcare needs. This study demonstrates that implementing CAD in TB ACF is both feasible and acceptable when supported by careful planning and adaptation to local contexts. Sustainable implementation hinges on technical support and the meaningful involvement of healthcare workers and communities, whose insights help ensure ethical and effective digital health innovation. The experience in Tondo offers lessons on deploying CAD in high-burden, resource-constrained settings.

Identifiers

PMID42848772
PMCPMC13649030

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.