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.

Journal: PloS one
PMID: 40215230

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.

Authors

  • Xiaolin Wei
    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China.
  • Dabin Liang
    Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi Zhuang Autonomous Region, China.
  • Zhitong Zhang
    Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Kevin E Thorpe
    Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Lingyun Zhou
    Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi Zhuang Autonomous Region, China.
  • Jinming Zhao
    Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi Zhuang Autonomous Region, China.
  • Huifang Qin
    Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi Zhuang Autonomous Region, China.
  • Xiaoyan Liang
    Reproductive Medicine Center, Sixth Affiliated Hospital, Sun Yat-Sen University, Shou Gou Ling Road, Guangzhou, 510000, China.
  • Zhezhe Cui
    Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Guangxi Key Laboratory of Major Infectious Disease Prevention and Control and Biosafety Emergency Response, Nanning, Guangxi Zhuang Autonomous Region, China.
  • Yan Huang
    Department of Neurology, University of Texas Health Science Center at Houston, Houston, TX.
  • Liwen Huang
    Department of Infectious Diseases, Shunde Hospital, Southern Medical University, Shunde, Guangdong, China.
  • Mei Lin
    State Key Laboratory of Oral Diseases, Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China.

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