AUTHOR=Hong Chuang-Yue , Wang Fu-Lin , Zhang You-Tong , Tao Feng-Xi , Ji Le-Cai , Lai Pei-Xuan , Li Ming-Zhen , Yang Chong-Guang , Tan Wei-Guo , Jiang Qi 

TITLE=Time-trend analysis of tuberculosis diagnosis in Shenzhen, China between 2011 and 2020

JOURNAL=Frontiers in Public Health

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1059433

DOI=10.3389/fpubh.2023.1059433

ISSN=2296-2565

ABSTRACT=Objective: To describe the trend of tuberculosis diagnosis in the migrant city Shenzhen, China, and to analyze the risk factors for diagnosis delays.
Methods: Demographic and clinical information of tuberculosis 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 (> 14 days from first care-seeking to tuberculosis diagnosis). The multivariable logistic regression was used to analyze the risk factors of diagnosis delays.
Results: During the study period, a total of 43,846 patients with active pulmonary tuberculosis were diagnosed and registered in Shenzhen. Averagely, the bacteriological positivity rate of the patients was 54.9%, and it increased from 38.6% in 2017 to 74.2% in 2020. Overall, 30.3% and 31.1% of patients had a patient delay and hospital delay, respectively. The molecular test significantly increased the bacteriological positivity and decreased the risk of hospital delay. Local residents had a higher risk of delays in both patient care-seeking and hospital diagnosis than migrants. Compared to 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 in the active case-finding of risk populations and optimization of molecular testing.