| 张业武,郭青,王晓风,于萌,苏雪梅,董言,张春曦.空间相对危险度估计方法在传染病风险评估中的应用[J].Chinese journal of Epidemiology,2015,36(5):531-534 |
| 空间相对危险度估计方法在传染病风险评估中的应用 |
| Application of spatial relative risk estimation in communicable disease risk evaluation |
| Received:September 01, 2014 |
| DOI：10.3760/cma.j.issn.0254-6450.2015.05.025 |
| KeyWord: 空间相对危险度 风险评估 可变带宽核密度估计 |
| English Key Word: Spatial relative risk Risk evaluation Adaptive kernel density estimation |
| FundProject:国家科技重大专项(2013ZX10004218-06-006) |
| Author Name | Affiliation | E-mail | | Zhang Yewu | Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Guo Qing | Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Wang Xiaofeng | Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Yu Meng | Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Su Xuemei | Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Dong Yan | Department of Information, Xinjiang Uygur Autonomous Regions Center for Disease Control and Prevention | | | Zhang Chunxi | Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China | zhangcx@chinacdc.cn |
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| Abstract: |
| 介绍可变带宽核密度算法、疾病空间相对危险度估计方法以及空间危险度统计学检验等在疾病风险评估中应用原理, 利用2013年云南省鲁甸及周边县区感染性腹泻病网络直报数据中其他感染性腹泻病的空间相对危险度进行估计并绘制疾病图。结果显示其他感染性腹泻病高风险热点区域主要集中于研究地区的东南部大片区域内, 表明基于可变带宽的核密度疾病空间风险度估计方法结合疾病制图技术, 可为确定重点防控人群和区域提供直观可视化的工具。 |
| English Abstract: |
| This paper summaries the application of adaptive kernel density algorithm in the spatial relative risk estimation of communicable diseases by using the reported data of infectious diarrhea (other than cholera, dysentery, typhoid and paratyphoid) in Ludian county and surrounding area in Yunnan province in 2013. Statistically significant fluctuations in an estimated risk function were identified through the use of asymptotic tolerance contours, and finally these data were visualized though disease mapping. The results of spatial relative risk estimation and disease mapping showed that high risk areas were in southeastern Shaoyang next to Ludian. Therefore, the spatial relative risk estimation of disease by using adaptive kernel density algorithm and disease mapping technique is a powerful method in identifying high risk population and areas. |
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