Evidence map›Paper›PMID 40971863›Full record

ArticleJMIR research protocols2025

Potential of the World Health Organization's Skin NTDs App to Support and Improve the Detection of Skin-Related Neglected Tropical Diseases: Protocol for a Performance Evaluation and Feasibility Study in Senegal.

Dior Sall, Dominik Jockers, Pauline Dioussé, Jonas Wachinger, Gilbert Batista, Jose Antonio Ruiz Postigo, Laurene Petitfour, Charlotte Robert, Bachir Mansour Diallo, Fulgence Abdou Faye and 12 more

Abstract read
In one paragraph

Article in JMIR research protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Independent assessment of the WHO Skin Neglected Tropical Diseases application for leprosy detection.Revista panamericana de salud publica = Pan American journal of public health · 2026
    Article
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

22 authors.

Dior Sall *Faculty of Medicine, Iba Der Thiam University of Thies, Thies, Senegal.ORCID 0009-0002-2725-2649
Dominik Jockers *Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.ORCID 0000-0001-7352-2772
Pauline DiousséFaculty of Medicine, Iba Der Thiam University of Thies, Thies, Senegal.ORCID 0009-0001-6991-9432
Jonas WachingerHeidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-5480-3138
Gilbert BatistaAction Damien, Dakar, Senegal.ORCID 0000-0003-1822-3571
Jose Antonio Ruiz PostigoPrevention, Treatment and Care Unit, Department of Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland.ORCID 0000-0002-7165-8358
Laurene PetitfourHeidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-9022-765X
Charlotte RobertHeidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.ORCID 0009-0005-5449-9024
Bachir Mansour DialloDepartment of Internal Medicine, Abdou Aziz Sy Hospital, Tivaouane, Senegal.ORCID 0000-0001-7574-4168
Fulgence Abdou FayeDepartment of Community Health, University of Alioune Diop de Bambey, Bambey, Senegal.ORCID 0009-0002-4123-7218
Yacine DiengGerman Leprosy and Tuberculosis Relief Association, DAHW, Dakar, Senegal.ORCID 0009-0006-3097-9960
Maresa NeuererHeidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.ORCID 0000-0001-8548-2085
Agbogbenkou Tevi Dela-Dem LawsonFaculty of Medicine, Iba Der Thiam University of Thies, Thies, Senegal.ORCID 0000-0003-1610-5651
Felicitas SchwermannGerman Leprosy and Tuberculosis Relief Association, DAHW, Würzburg, Germany.ORCID 0009-0000-8134-1525
Carme CarrionSchool of Health Sciences, Universitat de Girona, Girona, Spain.ORCID 0000-0003-1479-7551
Louis Hyacinthe ZoubiNational Leprosy Control Program, Dakar, Senegal.ORCID 0009-0007-3504-6681
Papa Mamadou DiagneAssociation Senegalaise de lutte contre la lèpre et les MTN, Dakar, Senegal.ORCID 0009-0009-8712-9037
Christa KasangGerman Leprosy and Tuberculosis Relief Association, DAHW, Würzburg, Germany.ORCID 0000-0003-0241-0321
Fatou Ndiaye Oumar SyDepartment of Community Health, University of Alioune Diop de Bambey, Bambey, Senegal.ORCID 0009-0008-0570-0846
Mahamath CisseGerman Leprosy and Tuberculosis Relief Association, DAHW, Dakar, Senegal.ORCID 0009-0003-6162-7982
Till Bärnighausen *Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany.ORCID 0000-0002-4182-4212
Madoky Diop *Faculty of Medicine, Iba Der Thiam University of Thies, Thies, Senegal.ORCID 0009-0000-0200-2710

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundThe World Health Organization (WHO) roadmap aims to control, eliminate, or eradicate neglected tropical diseases (NTDs) by promoting innovation in prevention, diagnosis, and treatment. In this context, mobile health (mHealth) tools could play an important role in improving health care across the globe, including for skin-related NTDs. One such tool is the WHO Skin NTDs App (currently available in its beta version), which utilizes artificial intelligence (AI) algorithms to classify skin lesion images and offers diagnostic suggestions and management information to bolster early detection at primary care levels. However, to harness the full potential of this and similar mHealth tools, additional insights into their diagnostic performance and potential implementation avenues in settings with limited access to trained dermatologists are essential.

objectiveThe objective of our mixed methods study is to test the functionality, operability, and potential of the AI-supported diagnostic component of the WHO Skin NTDs App (beta version) to support the detection of skin NTDs and common skin conditions in Senegal.

methodsWe are conducting a diagnostic accuracy study combined with a qualitative preimplementation usability exploration. For the quantitative component, we will collect and analyze approximately 800 skin lesion images from patients presenting to the dermatology unit at the Thiès regional hospital in Senegal. Each lesion will be independently assessed by the AI-based WHO Skin NTDs App and by a dermatologist who will provide a diagnosis serving as the reference standard. Performance metrics, including accuracy, sensitivity, specificity, precision, F

resultsWe expect the results to provide detailed insights into the feasibility and potential of the WHO Skin NTDs App to support and improve the detection of skin NTDs and common skin conditions at the community level in Senegal. We started data collection in August 2024, with the first results expected to be available in 2025.

conclusionsOur study will assess the performance and potential use of the WHO Skin NTDs App to detect skin NTDs and common skin conditions in Senegal, outlining its potential role in supporting early diagnoses and enhancing public health responses.

trial registrationGerman Clinical Trials Register DRKS00034297; https://drks.de/search/de/trial/DRKS00034297/details. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/69420.

Indexed as

Mobile ApplicationsNeglected DiseasesSkin DiseasesTropical MedicineArtificial IntelligenceFeasibility StudiesHumansSenegalTelemedicineWorld Health OrganizationAIartificial intelligencecapacity buildingcommunitycutaneousdiagnosticimage recognitionmHealthmobile healthperformance evaluationqualitative researchquantitative researchskin healthWest Africazero leprosy

Identifiers

PMID40971863
PMCPMC12495362

What Socratic holds

Textmetadata
LicenceCC BY
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.