Spatio-temporal analysis and risk assessment of multidrug-resistant tuberculosis in Guangdong Province, 2014—2019

doi:10.19982/j.issn.1000-6621.20240560

Abstract

Abstract:

Objective: To analyze the spatial and temporal distribution characteristics of multidrug resistant tuberculosis (MDR-TB) in Guangdong Province from 2014 to 2019, identify high-risk areas for MDR-TB and explore its influencing factors, so as to provide scientific basis and technical support for health department and governmental agencies. Methods: Basic data of MDR-TB patients registered in Guangdong Province from 2014 to 2019 was collected using the “Tuberculosis Information Management System”, a subsystem of the “China Information System for Disease Control and Prevention”. Related social and meteorological factors were collected and local weighted regression and spatial autocorrelation analysis were used to explore the spatial and temporal distribution of the incidence of MDR-TB; a two-stage zero-inflated Poisson model (ZIP) was established to analyze influencing factors associated with the incidence of MDR-TB. Results: During the period of 2014—2019, a total of 3358 MDR-TB patients were registered in Guangdong Province, with an average annual registered incidence rate of 0.47/100000 (3358/720530000); temporally the registered MDR-TB cases in Guangdong Province showed a statistically significant trend of increasing ( $χ t r e n d 2$ =158.980, P<0.001), with a registered incidence rate of 0.20/100000 in 2014 (233/114890000) increased to 0.53/100000 (667/124890000) in 2019, and the onset of the disease was mostly concentrated in the fall and winter seasons. Spatially, higher mean SIR were identified in Shenzhen, Dongguan, and Guangzhou (2.36, 2.36, and 1.74, respectively). The ZIP model showed that the risk of MDR-TB incidence was positively associated with relative humidity (RR=1.168, 95%CI: 1.031-1.323), sex ratio (RR=1.312, 95%CI: 1.192-1.473), and proportion of floating population (RR=1.176, 95%CI: 1.094-1.263), and was negatively associated with nighttime light index (RR=0.752, 95%CI: 0.668-0.848) and medical beds per 1000 population (RR=0.672, 95%CI: 0.589-0.776). Conclusion: MDR-TB morbidity has temporal and spatial distribution differences and is significantly associated with socio-economic and meteorological factors. Public health interventions, TB control strategies and resource allocation should be implemented in high-risk areas and high-risk populations accordingly in the future.

Key words: Tuberculosis, multidrug-resistant, Factor analysis, statistical, Space-time clustering

CLC Number:

R52
R181.3

Hu Yijun, Xu Yiting, Jian Ronghua, Wu Huizhong, Su Jing, Xiao Jianpeng, Jiang Chenqi, Liu Tao, Wang Jiawen, Chen Liang. Spatio-temporal analysis and risk assessment of multidrug-resistant tuberculosis in Guangdong Province, 2014—2019[J]. Chinese Journal of Antituberculosis, 2025, 47(5): 639-646. doi: 10.19982/j.issn.1000-6621.20240560

Figures/Tables 8

References 37

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年份	Moran’s I值	E(I)	Z值	P值
2014	0.35	-0.01	6.04	<0.001
2015	0.56	-0.01	9.70	<0.001
2016	0.24	-0.01	4.25	<0.001
2017	0.26	-0.01	4.92	<0.001
2018	0.48	-0.01	8.20	<0.001
2019	0.45	-0.01	7.72	<0.001

城市	平均SIR值	城市	平均SIR值
广州	1.74	惠州	1.55
韶关	0.40	梅州	0.43
深圳	2.36	汕尾	0.20
珠海	0.82	河源	0.17
汕头	1.59	阳江	1.05
佛山	1.43	清远	0.74
江门	1.11	东莞	2.36
湛江	0.13	中山	1.57
茂名	0.36	潮州	0.53
肇庆	0.66	揭阳	0.33

类型	DIC	WAIC
ZIP模型
Type1	3087.58	2850.67
Type2	2831.33	2767.60
Type3	2762.62	2476.38
Possion模型
Type1	3131.34	3181.52
Type2	2894.22	2817.71
Type3	2795.58	2582.58

变量	后验均值	2.5%	97.5%	RR(95%CI)值	P值
气象因素
月平均气温	0.002	-0.136	0.145	1.002(0.872~1.156)	0.341
月平均相对湿度	0.156	0.030	0.280	1.168(1.031~1.323)	<0.001
月平均风速	0.024	0.078	0.127	1.024(0.925~1.136)	0.254
月平均日照时数	-0.002	-0.140	0.136	0.998(0.869~1.145)	0.429
社会经济因素
性别比	0.272	0.176	0.388	1.312(1.192~1.473)	<0.001
流动人口比例	0.163	0.090	0.233	1.176(1.094~1.263)	<0.001
教育支出占财政比例	0.100	-0.245	0.068	0.905(0.783~1.070)	0.153
每千人病床数	-0.285	-0.404	-0.165	0.752(0.668~0.848)	<0.001
夜间灯光指数	-0.398	-0.529	-0.254	0.672(0.589~0.776)	<0.001
人均GDP	-0.165	-0.350	0.036	0.848(0.705~1.036)	0.547