NYMC Faculty Publications

Iterative Evaluation of Mobile Computer-Assisted Digital Chest X-Ray Screening for Tb Improves Efficiency, Yield, and Outcomes in Nigeria

Authors

Rupert A. Eneogu, United States Agency for International Development (USAID), Abuja, Nigeria.
Ellen M. Mitchell, Mycobacterial Diseases and Neglected Tropical Diseases Unit, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.
Chidubem Ogbudebe, KNCV TB Foundation, Abuja, Nigeria.
Danjuma Aboki, Nasarawa State TB and Leprosy Control Program, Nasarawa, Nigeria.
Victor Anyebe, KNCV TB Foundation, Abuja, Nigeria.
Chimezie B. Dimkpa, KNCV TB Foundation, Abuja, Nigeria.
Daniel Egbule, Nasarawa State TB and Leprosy Control Program, Nasarawa, Nigeria.
Bassey Nsa, McMaster University, Ontario, Canada.
Emmy van der Grinten, KNCV TB Foundation, The Hague, Netherlands.
Festus O. Soyinka, Ogun State Ministry of Health, Ogun, Nigeria.
Hussein Abdur-Razzaq, Lagos State Ministry of Health, Lagos, Nigeria.Follow
Sani Useni, KNCV TB Foundation, Abuja, Nigeria.
Adebola Lawanson, National TB and Leprosy Program, Federal Ministry of Health Nigeria, Abuja, Nigeria.
Simeon Onyemaechi, National TB and Leprosy Program, Federal Ministry of Health Nigeria, Abuja, Nigeria.
Emperor Ubochioma, National TB and Leprosy Program, Federal Ministry of Health Nigeria, Abuja, Nigeria.
Jerod Scholten, KNCV TB Foundation, The Hague, Netherlands.
Johan Verhoef, KNCV TB Foundation, The Hague, Netherlands.
Peter Nwadike, KNCV TB Foundation, The Hague, Netherlands.
Nkemdilim Chukwueme, New York Medical College, New York, NY, United States of America.
Debby Nongo, United States Agency for International Development (USAID), Abuja, Nigeria.
Mustapha Gidado, KNCV TB Foundation, The Hague, Netherlands.

Author Type(s)

Faculty

DOI

10.1371/journal.pgph.0002018

Journal Title

PLoS Global Public Health

First Page

e0002018

Document Type

Article

Publication Date

1-1-2024

Department

Public Health

Abstract

Wellness on Wheels (WoW) is a model of mobile systematic tuberculosis (TB) screening of high-risk populations combining digital chest radiography with computer-aided automated detection (CAD) and chronic cough screening to identify presumptive TB clients in communities, health facilities, and prisons in Nigeria. The model evolves to address technical, political, and sustainability challenges. Screening methods were iteratively refined to balance TB yield and feasibility across heterogeneous populations. Performance metrics were compared over time. Screening volumes, risk mix, number needed to screen (NNS), number needed to test (NNT), sample loss, TB treatment initiation and outcomes. Efforts to mitigate losses along the diagnostic cascade were tracked. Persons with high CAD4TB score (≥80), who tested negative on a single spot GeneXpert were followed-up to assess TB status at six months. An experimental calibration method achieved a viable CAD threshold for testing. High risk groups and key stakeholders were engaged. Operations evolved in real time to fix problems. Incremental improvements in mean client volumes (128 to 140/day), target group inclusion (92% to 93%), on-site testing (84% to 86%), TB treatment initiation (87% to 91%), and TB treatment success (71% to 85%) were recorded. Attention to those as highest risk boosted efficiency (the NNT declined from 8.2 ± SD8.2 to 7.6 ± SD7.7). Clinical diagnosis was added after follow-up among those with ≥ 80 CAD scores and initially spot -sputum negative found 11 additional TB cases (6.3%) after 121 person-years of follow-up. Iterative adaptation in response to performance metrics foster feasible, acceptable, and efficient TB case-finding in Nigeria. High CAD scores can identify subclinical TB and those at risk of progression to bacteriologically-confirmed TB disease in the near term.

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