Comprehensive assessment of Keshan disease based on a geographic information system / 中国地方病学杂志
Chinese Journal of Endemiology
;
(6): 437-440, 2012.
Artículo
en Chino
| WPRIM
| ID: wpr-643271
ABSTRACT
Objective To explore the spatial distribution of Keshan disease(KD) in the 15 surveillance provinces(municipalities,autonomous regions ) and to provide the basis for the development of prevention and control strategies.MethodsBased on the KD surveillance data of the 15 provinces in 2007,five indicators were selected.Moreover,a comprehensive indicator score to assess KD of different areas was made through the method of principle components analysis,which was applied for regionalization of the KD areas by the subsection method of standard deviation in whole China.The KD areas were divided into mild,moderate and severe endemic areas.The spatial distribution feature of the comprehensive indicator score was displayed by using geographic information system (GIS).ResultsThe three principal components contained 88.123% information of all the selected indicators,the first principal component had a close relationship with total KD detection rate,chronic KD detection rate and latent KD detection rate; the second principal component had a close relationship with the threatened number in KD areas,and the third principal component had a close relationship with new KD detection rate; the comprehensive indicator indicates that Gansu,Jilin,Heilongjiang,Hebei,and Liaoning provinces were serious prevalent KD areas; Inner Mongolia,Shandong,Hubei,Sichuang provinces (autonomous region) were moderate prevalent KD areas,and Shanxi,Shaanxi,Yunnan,Henan,Guizhou,Chongqing provinces(municipality)were mild prevalent KD areas.Conclusions The introduction of the GIS to Keshan disease monitoring,provides a convenient and direct method to observe the spatial distribution of the disease,and the results point out the key areas for further KD surveillance according to local conditions.
Texto completo:
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Índice:
WPRIM (Pacífico Occidental)
Idioma:
Chino
Revista:
Chinese Journal of Endemiology
Año:
2012
Tipo del documento:
Artículo
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