Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: May 23, 2023
Date Accepted: Aug 12, 2024
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Changes in newly notified cases and control of tuberculosis in Fujian Province, 2005–2021: a spatial-temporal analysis of surveillance data
ABSTRACT
Background:
The unbalanced temporal and spatial trends of pulmonary tuberculosis (PTB) risk at a fine level in Fujian Province remain unclear.
Objective:
To identify the PTB epidemic status in past and recent years to provide some information for further PTB control in Fujian Province.
Methods:
Prefectural-level and county-level notified PTB case data were collected in Fujian Province. A Joinpoint regression model was constructed to analyze the unbalanced temporal patterns of PTB notification rates from 2005 to 2021 at prefecture-level city scales. The spatial clustering analysis and spatial autocorrelation analysis were performed to assess the inequality of the locations of PTB cases. Demographical characteristics were explored by the method of descriptive analysis.
Results:
A total of 357,838 cases of PTB were reported in Fujian Province from 2005 to 2021. The PTB notification rate in the eastern and southern regions were significantly higher than those in the northern, western and central areas (P<.001). Ningde City had the highest PTB notification rate, with a multiyear average of 69.2/100,000, followed by Quanzhou City (68.6/100,000) and Xiamen City (64.2/100,000). Nanping City (APC -14.1, 95% CI -28.2 to 2.6; P<.001) and Xiamen City (APC -13.4, 95% CI -19.5 to -6.9; P<.001) experienced the fastest declines. The spring-summer predominance of PTB incidence was observed in the study years. Unsupervised hierarchical clustering allowed the classification of 9 cities in Fujian for two clusters and five clusters further based on 83 counties. Risks of infection show positive spatial autocorrelation, but the geographical distribution of local spatial autocorrelation differs significantly among different years and cities. Hot spots were mainly located in the east and south, and cold spots were in the northern areas. The highest burden of all PTB cases was among males, middle to old-age adult men (more than 45 years old), and farmers, and it was the same for the situation of pathogen-positive TB or pathogen-negative TB.
Conclusions:
Our study revealed the differences in tuberculosis notification rates between and within prefecture-level cities over time and smear status. Given the natural history of TB, equitable improvements in case detection for high-risk groups are vital to reducing the overall disease burden in a population.
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