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.
<h4>Background</h4>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...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316073 |
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| author | Xiaolin Wei Dabin Liang Zhitong Zhang Kevin E Thorpe Lingyun Zhou Jinming Zhao Huifang Qin Xiaoyan Liang Zhezhe Cui Yan Huang Liwen Huang Mei Lin |
| author_facet | Xiaolin Wei Dabin Liang Zhitong Zhang Kevin E Thorpe Lingyun Zhou Jinming Zhao Huifang Qin Xiaoyan Liang Zhezhe Cui Yan Huang Liwen Huang Mei Lin |
| author_sort | Xiaolin Wei |
| collection | DOAJ |
| description | <h4>Background</h4>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.<h4>Methods</h4>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.<h4>Discussion</h4>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.<h4>Trial registration</h4>ClinicalTrials.gov NCT06702774. |
| format | Article |
| id | doaj-art-6dfd0880c81a4310bfb2f757b5cdb307 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-6dfd0880c81a4310bfb2f757b5cdb3072025-08-20T03:14:08ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01204e031607310.1371/journal.pone.0316073Active 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.Xiaolin WeiDabin LiangZhitong ZhangKevin E ThorpeLingyun ZhouJinming ZhaoHuifang QinXiaoyan LiangZhezhe CuiYan HuangLiwen HuangMei Lin<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Discussion</h4>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.<h4>Trial registration</h4>ClinicalTrials.gov NCT06702774.https://doi.org/10.1371/journal.pone.0316073 |
| spellingShingle | Xiaolin Wei Dabin Liang Zhitong Zhang Kevin E Thorpe Lingyun Zhou Jinming Zhao Huifang Qin Xiaoyan Liang Zhezhe Cui Yan Huang Liwen Huang Mei Lin 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. PLoS ONE |
| title | 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. |
| title_full | 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. |
| title_fullStr | 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. |
| title_full_unstemmed | 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. |
| title_short | 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. |
| title_sort | 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 |
| url | https://doi.org/10.1371/journal.pone.0316073 |
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