ArticleFrontiers in public health2023
Time-trend analysis of tuberculosis diagnosis in Shenzhen, China between 2011 and 2020.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Risk Factors Associated With Tuberculosis Diagnostic Delay in the Jiangsu Province, China (2011-2021): Spatiotemporal Database Analysis Study.JMIR public health and surveillance · 2026Article
- Eight-year tuberculosis epidemic trends in the Republic of Congo, a high TB burden country: progress and gaps towards end-TB targets.BMJ global health · 2025Article
- Trend analysis of changes in the incidence of tuberculosis in Shenzhen from 2010 to 2020 based on the Joinpoint regression model.BMC public health · 2025Article
- Analyzing factors affecting tuberculosis incidence in various mainland Chinese economic regions and predicting trends: a comprehensive regression study.BMC public health · 2025Article
- Targeted next-generation sequencing: a promising approach forMicrobiology spectrum · 2025Article
- Latent tuberculosis infection in China, 1990-2050: GBD-informed projections for age-targeted screening.Frontiers in public health · 2025Article
- Analysis of diagnosis delay among migrant pulmonary tuberculosis patients in Guangzhou from 2014 to 2022.Frontiers in public health · 2025Article
- Household economic burden and catastrophic expenditures in non-resistant tuberculosis patients: cross-sectional survey in Guizhou, China.Frontiers in public health · 2025Article
- Article
- Trends in the Notification Rates and Treatment Outcome of Tuberculosis in Shandong Province, China, 2005-2021.Infection and drug resistance · 2024Article
- Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China.Frontiers in public health · 2024Article
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10 authors.
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Abstract
Objective: To describe the trend of tuberculosis (TB) diagnosis in the migrant city Shenzhen, China, and analyze the risk factors of diagnosis delays. Methods: Demographic and clinical information of TB patients from 2011 to 2020 in Shenzhen were extracted. A bundle of measures to enhance TB diagnosis had been implemented since late 2017. We calculated the proportions of patients who underwent a patient delay (>30 days from syndrome onset to first care-seeking) or a hospital delay (>4 days from first care-seeking to TB diagnosis). Multivariable logistic regression was used to analyze the risk factors of diagnosis delays. Results: During the study period, 43,846 patients with active pulmonary TB were diagnosed and registered in Shenzhen. On average, the bacteriological positivity rate of the patients was 54.9%, and this increased from 38.6% in 2017 to 74.2% in 2020. Overall, 30.3 and 31.1% of patients had a patient delay or a hospital delay, respectively. Molecular testing significantly increased bacteriological positivity and decreased the risk of hospital delay. People >35 years old, the unemployed, and residents had a higher risk of delays in both patient care-seeking and hospital diagnosis than younger people, workers, or migrants. Compared with passive case-finding, active case-finding significantly decreased the risk of patient delay by 5.47 (4.85-6.19) times. Conclusion: The bacteriological positivity rate of TB patients in Shenzhen increased significantly but the diagnosis delays were still serious, which may need more attention when active case-finding in risk populations and optimization of molecular testing.
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