Application of spatial relative risk estimation in communicable disease risk evaluation

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 provin...

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Bibliographic Details
Published inZhōnghuá liúxíngbìng zázhì Vol. 36; no. 5; p. 531
Main Authors Zhang, Yewu, Guo, Qing, Wang, Xiaofeng, Yu, Meng, Su, Xuemei, Dong, Yan, Zhang, Chunxi
Format Journal Article
LanguageChinese
Published China 01.05.2015
Subjects
Algorithms
China - epidemiology
Communicable Diseases - epidemiology
Dysentery - epidemiology
Humans
Reproducibility of Results
Risk
Risk Assessment - methods
Spatial Analysis
China
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Summary: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.
ISSN:0254-6450