Qi Wang1, Liang Guo2, Jing Wang3, Leijie Zhang1, Wanqi Zhu1, Yan Yuan1, Juansheng Li1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Lanzhou University, Lanzhou, China. 2. The Second School of Clinical Medicine, Lanzhou University, Lanzhou, China. 3. Nursing Department of the First Hospital of Lanzhou University, Lanzhou, China.
Abstract
BACKGROUND: To assess the spatial epidemic characteristics of TB and identify the key areas for disease prevention and control. OBJECTIVE: To explore the spatial distribution and socioeconomic influencing factors of TB in mainland China from 2013 to 2016. METHODS: Spatial autocorrelation was used to explore the spatial distribution characteristics of TB at the quantitative level. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were conducted to explore the association between factors and TB incidence from both global and local perspectives. RESULTS: There was a significant positive spatial autocorrelation of TB at the provincial level (P < 0.05): hot spots were mainly located in the west of Xinjiang and Tibet, and cold spots in the eastern coastal areas. Four latent factors on the socioeconomic dimension, involving the proportion of illiterate people aged 15 and over, per capita disposable income in rural areas, the number of health technicians per 1000 population and the urban population density, were associated with TB incidence. The GWR model showed that the effect of the same factor on TB incidence varied with geographical location. CONCLUSIONS: Spatial clustering of TB incidence in mainland China still exists. The differences of socioeconomic factors in different locations can be confirmed by GWR model. Targeted preventive and control measures or policies will be conducive in effectively reducing the incidence of TB, especially in hot spots.
BACKGROUND: To assess the spatial epidemic characteristics of TB and identify the key areas for disease prevention and control. OBJECTIVE: To explore the spatial distribution and socioeconomic influencing factors of TB in mainland China from 2013 to 2016. METHODS: Spatial autocorrelation was used to explore the spatial distribution characteristics of TB at the quantitative level. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were conducted to explore the association between factors and TB incidence from both global and local perspectives. RESULTS: There was a significant positive spatial autocorrelation of TB at the provincial level (P < 0.05): hot spots were mainly located in the west of Xinjiang and Tibet, and cold spots in the eastern coastal areas. Four latent factors on the socioeconomic dimension, involving the proportion of illiterate people aged 15 and over, per capita disposable income in rural areas, the number of health technicians per 1000 population and the urban population density, were associated with TB incidence. The GWR model showed that the effect of the same factor on TB incidence varied with geographical location. CONCLUSIONS: Spatial clustering of TB incidence in mainland China still exists. The differences of socioeconomic factors in different locations can be confirmed by GWR model. Targeted preventive and control measures or policies will be conducive in effectively reducing the incidence of TB, especially in hot spots.
Authors: Joconiah Chirenda; Isaiah Gwitira; Robin M Warren; Samantha L Sampson; Amon Murwira; Collen Masimirembwa; Kudzanai M Mateveke; Cremence Duri; Prosper Chonzi; Simbarashe Rusakaniko; Elizabeth M Streicher Journal: PLoS One Date: 2020-04-21 Impact factor: 3.240