The characteristics of spatial-temporal distribution and cluster of tuberculosis in Yunnan Province, China, 2005\u20132018

Jinou Chen,Kunyun Lu,Rui Yang,Lin Xu,Yubing Qiu,Ling Li,Jinglong Hou

doi:10.1186/s12889-019-7993-5

Jinou Chen, Kunyun Lu + Show 5 more

Open Access

https://doi.org/10.1186/s12889-019-7993-5

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Abstract

BackgroundTuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. Meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS.MethodsData for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff’s space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS.ResultThere were a total of 381,855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100,000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR = 2.6, P < 0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS.ConclusionThis study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.

Highlights

Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS)
Spatial-temporal scan statistics detected the significant clusters of pulmonary tuberculosis (PTB) prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR = 2.6, P < 0.01), though the most recent cluster for PTB and spatial cluster for sputum smear-positive tuberculosis (SSP-TB) was in borders with GMS
Temporal distribution and clusters From 2005 to 2018, a total of 381,855 PTB cases were notified in Yunnan

Summary

Introduction

Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). TB made a big challenge to public health especially in high disease burden counties [1, 2]. Yunnan Province followed the National Tuberculosis Control Program in China (China NTP), yet implemented non-routine strategy of active case finding to detect TB cases in hard-to-reach population among few communities [8]. This public health action may have an impact on local TB epidemic status and made it a challenge to describe and understand the trend of TB prevalence

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