Spatial statistical and environmental correlation analyses on vector density, vector infection index and Japanese encephalitis cases at the village and pigsty levels in Liyi County, Shanxi Province, China

被引:5
作者
Liu, Mei-De [1 ]
Li, Chun-Xiao [1 ]
Cheng, Jing-Xia [2 ]
Zhao, Tong-Yan [1 ]
机构
[1] Acad Mil Med Sci, State Key Lab Pathogen & Biosecur, Beijing 100071, Peoples R China
[2] Shanxi Ctr Dis Control & Prevent, Taiyuan 030012, Shanxi, Peoples R China
基金
美国国家科学基金会;
关键词
Mosquito vector; Japanese encephalitis; Environment; Pigsty; Spatial analysis; WEST-NILE-VIRUS; SEASONAL PREVALENCE; MOSQUITO VECTORS; RISK-FACTORS; ABUNDANCE; DISTRICT;
D O I
10.1186/s13071-022-05305-8
中图分类号
R38 [医学寄生虫学]; Q [生物科学];
学科分类号
07 ; 0710 ; 09 ; 100103 ;
摘要
Background: In the eco-epidemiological context of Japanese encephalitis (JE), geo-environmental features influence the spatial spread of the vector (Culex tritaeniorhynchus, Giles 1901) density, vector infection, and JE cases. Methods: In Liyi County, Shanxi Province, China, the spatial autocorrelation of mosquito vector density, vector infection indices, and JE cases were investigated at the pigsty and village scales. The map and Enhanced Thematic Mapper (ETM) remote sensing databases on township JE cases and geo-environmental features were combined in a Geographic Information System (GIS), and the connections among these variables were analyzed with regression and spatial analyses. Results: At the pigsty level, the vector density but not the infection index of the vector was spatially autocorrelated. For the pigsty vector density, the cotton field area was positively related, whereas the road length and the distance between pigsties and gullies were negatively related. In addition, the vector infection index was correlated with the pigsty vector density (PVD) and the number of pigs. At the village level, the vector density, vector infection index, and number ofJE cases were not spatially autocorrelated. In the study area, the geo-environmental features, vector density, vector infection index, and JE case number comprised the Geo-Environment-Vector-JE (GEVJ) intercorrelation net system. In this system, pig abundance and cotton area were positive factors influencing the vector density first. Second, the infection index was primarily influenced by the vector density. Lastly, the JE case number was determined by the vector infection index and the wheat area. Conclusions: This study provided quantitative associations among geo-environmental features, vectors, and the incidence of JE in study sties, one typical northern Chinese JE epidemiological area without rice cultivation. The results highlighted the importance of using a diverse range of environmental management methods to control mosquito disease vectors and provided useful information for improving the control of vector mosquitoes and reducing the incidence of JE in the northern Chinese agricultural context.
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页数:11
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