Modeling tuberculosis transmission flow in China, 2010-2012
文献类型：期刊论文
| 作者 | Wang, Li1,3; Xu, Chengdong2; Hu, Maogui2; Wang, Jinfeng2; Qiao, Jiajun1,3; Chen, Wei4; Zhu, Qiankun1; Wang, Zhipeng1 |
| 刊名 | BMC INFECTIOUS DISEASES
 |
| 出版日期 | 2024-08-05 |
| 卷号 | 24期号:1页码:784 |
| 关键词 | Floating population Tuberculosis flow Spatial interaction model Socioeconomic determinants |
| DOI | 10.1186/s12879-024-09649-7 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | BackgroundChina has the third largest number of TB cases in the world, and the average annual floating population in China is more than 200 million, the increasing floating population across regions has a tremendous potential for spreading infectious diseases, however, the role of increasing massive floating population in tuberculosis transmission is yet unclear in China.Methods29,667 tuberculosis flow data were derived from the new smear-positive pulmonary tuberculosis cases in China. Spatial variation of TB transmission was measured by geodetector q-statistic and spatial interaction model was used to model the tuberculosis flow and the regional socioeconomic factors.ResultsTuberculosis transmission flow presented spatial heterogeneity. The Pearl River Delta in southern China and the Yangtze River Delta along China's east coast presented as the largest destination and concentration areas of tuberculosis inflows. Socioeconomic factors were determinants of tuberculosis flow. Some impact factors showed different spatial associations with tuberculosis transmission flow. A 10% increase in per capita GDP was associated with 10.2% in 2010 or 2.1% in 2012 decrease in tuberculosis outflows from the provinces of origin, and 1.2% in 2010 or 0.5% increase in tuberculosis inflows to the destinations and 18.9% increase in intraprovincial flow in 2012. Per capita net income of rural households and per capita disposable income of urban households were positively associated with tuberculosis flows. A 10% increase in per capita net income corresponded to 14.0% in 2010 or 3.6% in 2012 increase in outflows from the origin, 44.2% in 2010 or 12.8% increase in inflows to the destinations and 47.9% increase in intraprovincial flows in 2012. Tuberculosis incidence had positive impacts on tuberculosis flows. A 10% increase in the number of tuberculosis cases corresponded to 2.2% in 2010 or 1.1% in 2012 increase in tuberculosis inflows to the destinations, 5.2% in 2010 or 2.0% in 2012 increase in outflows from the origins, 11.5% in 2010 or 2.2% in 2012 increase in intraprovincial flows.ConclusionsTuberculosis flows had clear spatial stratified heterogeneity and spatial autocorrelation, regional socio-economic characteristics had diverse and statistically significant effects on tuberculosis flows in the origin and destination, and income factor played an important role among the determinants. |
| WOS关键词 | SPATIAL-ANALYSIS ; MIGRATION ; MIGRANTS ; HETEROGENEITY ; URBANIZATION ; DYNAMICS ; DRIVERS ; DISEASE |
| WOS研究方向 | Infectious Diseases |
| WOS记录号 | WOS:001284704000007 |
| 出版者 | BMC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/206908]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Wang, Jinfeng; Qiao, Jiajun |
| 作者单位 | 1.Henan Univ, Coll Geog & Environm Sci, Kaifeng 475001, Peoples R China 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China 4.Chinese Ctr Dis Control & Prevent, Beijing 102206, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Li,Xu, Chengdong,Hu, Maogui,et al. Modeling tuberculosis transmission flow in China, 2010-2012[J]. BMC INFECTIOUS DISEASES,2024,24(1):784. |
| APA | Wang, Li.,Xu, Chengdong.,Hu, Maogui.,Wang, Jinfeng.,Qiao, Jiajun.,...&Wang, Zhipeng.(2024).Modeling tuberculosis transmission flow in China, 2010-2012.BMC INFECTIOUS DISEASES,24(1),784. |
| MLA | Wang, Li,et al."Modeling tuberculosis transmission flow in China, 2010-2012".BMC INFECTIOUS DISEASES 24.1(2024):784. |
入库方式： OAI收割
来源：地理科学与资源研究所
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