Active case finding using mobile vans with artificial intelligence aided radiology tests and sputum collection for rapid diagnostic tests to reduce tuberculosis prevalence among high-risk population in rural China: Protocol for a pragmatic trial

X Xiaolin Wei D Dabin Liang Z Zhitong Zhang K Kevin E. Thorpe L Lingyun Zhou J Jinming Zhao H Huifang Qin X Xiaoyan Liang Z Zhezhe Cui Y Yan Huang L Liwen Huang (Department of Applied Biology and Chemical Technology, Food Safety and Technology Research Centre, and Research Centre for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon 999077, Hong Kong SAR, China) M Mei Lin

Abstract

Background Tuberculosis (TB) remains a significant public health challenge, particularly in rural areas of high-burden countries like China. Active case finding (ACF) and timely treatment have been proven effective in reducing TB prevalence, but the impact on the TB epidemic when employing new technologies in ACF is still unknown. This study aims to evaluate the effectiveness of a comprehensive ACF package utilizing mobile vans equipped with artificial intelligence (AI)-aided radiology and GeneXpert testing in reducing TB prevalence among high-risk populations in rural Guangxi, China. Methods A pragmatic cluster randomized controlled trial will be conducted in two counties of Guangxi, China. The trial will randomize 23 townships to intervention or control groups at approximately 1:1 ratio. The intervention group will receive an ACF campaign in Year 1 among high-risk populations, incorporating visited by mobile vans equipped with AI-based digital X-ray screening, symptom assessment, and sputum collection for GeneXpert testing. Control group participants receive usual care. TB patients identified in Year 1 will complete their treatment in Year 2. The primary outcome is the prevalence rate of bacteriologically confirmed TB among high-risk populations in Year 3. Process evaluation will explore acceptability, feasibility and adaptation of the intervention. We will conduct incremental costing study to inform future scale-up of the intervention in other settings. Discussion This study will provide valuable insights into the effectiveness and feasibility of utilizing AI-equipped mobile vans and GeneXpert for TB ACF to reduce TB prevalence in rural settings. If successful, this model will contribute to possible solutions to achieve the WHO End TB Strategy by 2035. Trial registration ClinicalTrials.gov NCT06702774

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 4
Published April 11, 2025
Pages e0316073
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (12)

X

Xiaolin Wei

D

Dabin Liang

Z

Zhitong Zhang

K

Kevin E. Thorpe

L

Lingyun Zhou

J

Jinming Zhao

H

Huifang Qin

X

Xiaoyan Liang

Z

Zhezhe Cui

Y

Yan Huang

L

Liwen Huang

Department of Applied Biology and Chemical Technology, Food Safety and Technology Research Centre, and Research Centre for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon 999077, Hong Kong SAR, China

M

Mei Lin