Analysis of spatial-temporal distribution and influencing factors of pulmonary tuberculosis in China, during 2008–2015. (10th October 2018)

• Record Type: Journal Article
• Authors: Zhang, Y.; Wang, X. L.; Feng, T.; Fang, C. Z.
• Is Part Of: Epidemiology and infection. Volume 147(2019)
• Publication Date: 2018-10-10
• Subjects: Incidence, -- influencing factors, -- pulmonary tuberculosis, -- spatial aggregation; Communicable diseases -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1017/S0950268818002765
• Languages: English
• ISSNs: 0950-2688

Abstract

Abstract: At present, the number of people with tuberculosis in China is second only to India and ranks second in the world. Under such a severe case of tuberculosis in China, prevention and control of pulmonary tuberculosis are urgently needed. This study aimed to study the temporal and geographical relevance of the pathogenesis of pulmonary tuberculosis and the factors affecting the incidence of tuberculosis. Spatial autocorrelation model was used to study the spatial distribution characteristics of pulmonary tuberculosis from a quantitative level. The research results showed that the overall incidence of pulmonary tuberculosis (IPT) in China was low in the east, high in the west and had certain seasonal characteristics. We use Spatial Lag Model to explore influencing factors of pulmonary tuberculosis. It indicates that the IPT is high in areas with underdeveloped economics, poor social services and low average smoking ages. Additionally, the IPT is high in areas with high AIDS prevalence. Also, compared with Classical Regression Model and Spatial Error Model, our model has smaller values of Akaike information criterion and Schwarz criterion. Besides, our model has bigger values of coefficient of determination ( R 2 ) and log-likelihood (log L ) than the other two models. Apart from that, it is more significant than Spatial Error Models in the spatial dependence test for the IPT.