Spatiotemporal Variation and Hot Spot Detection of Visceral Leishmaniasis Disease in Kashi Prefecture, China

Canjun Zheng, Jingying Fu, Zeng Li, Gang Lin, Dong Jiang and Xiao-nong Zhou
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Canjun Zheng: Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China
Jingying Fu: State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Zeng Li: College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
Gang Lin: College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
Dong Jiang: State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiao-nong Zhou: National Institute for Parasitic Diseases, Chinese Center for Disease Control and Prevention (China CDC), Shanghai 200025, China

IJERPH, 2018, vol. 15, issue 12, 1-11

Abstract: Visceral leishmaniasis (VL) remains a serious public health problem in China. To explore the temporal, spatial, and spatiotemporal characteristics of visceral leishmaniasis (VL), the spatial and spatiotemporal clustering distribution and their relationships with the surrounding geographic environmental factors were analyzed. In this study, the average nearest-neighbor distance (ANN), Ripley’s K-function and Moran’s I statistics were used to evaluate spatial autocorrelation in the VL distribution of the existing case patterns. Getis–Ord Gi* was used to identify the hot-spot and cold-spot areas based on Geographic Information System (GIS), and spatiotemporal retrospective permutation scan statistics was used to detect the spatiotemporal clusters. The results indicated that VL continues to be a serious public health problem in Kashi Prefecture, China, particularly in the north-central region of Jiashi County, which is a relatively high-risk area in which hot spots are distributed. Autumn and winter months were the outbreak season for VL cases. The detection of spatial and spatiotemporal patterns can provide epidemiologists and local governments with significant information for prevention measures and control strategies.

Keywords: GIS; hot spots; spatiotemporal clusters; Kashi Prefecture (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
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