Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis

Xing Zhao, Mingqin Cao, Hai-Huan Feng, Heng Fan, Fei Chen, Zijian Feng, Xiaosong Li and Xiao-Hua Zhou
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Xing Zhao: West China School of Public Health, Sichuan University, Chengdu 610041, China
Mingqin Cao: School of Public Health, Xinjiang Medical University, Urumqi 830011, China
Hai-Huan Feng: West China School of Public Health, Sichuan University, Chengdu 610041, China
Heng Fan: West China School of Public Health, Sichuan University, Chengdu 610041, China
Fei Chen: West China School of Public Health, Sichuan University, Chengdu 610041, China
Zijian Feng: Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention (China CDC), Beijing 102206, China
Xiaosong Li: West China School of Public Health, Sichuan University, Chengdu 610041, China
Xiao-Hua Zhou: Department of Biostatistics, School of Public Health, University of Washington,Seattle, WA 98195, USA

IJERPH, 2014, vol. 11, issue 4, 1-17

Abstract: It is valuable to study the spatiotemporal pattern of Japanese encephalitis (JE) and its association with the contextual risk factors in southwest China, which is the most endemic area in China. Using data from 2004 to 2009, we applied GISmapping and spatial autocorrelation analysis to analyze reported incidence data of JE in 438 counties in southwest China, finding that JE cases were not randomly distributed, and a Bayesian hierarchical spatiotemporal model identified the east part of southwest China as a high risk area. Meanwhile, the Bayesian hierarchical spatial model in 2006 demonstrated a statistically significant association between JE and the agricultural and climatic variables, including the proportion of rural population, the pig-to-human ratio, the monthly precipitation and the monthly mean minimum and maximum temperatures. Particular emphasis was placed on the time-lagged effect for climatic factors. The regression method and the Spearman correlation analysis both identified a two-month lag for the precipitation, while the regression method found a one-month lag for temperature. The results show that the high risk area in the east part of southwest China may be connected to the agricultural and climatic factors. The routine surveillance and the allocation of health resources should be given more attention in this area. Moreover, the meteorological variables might be considered as possible predictors of JE in southwest China.

Keywords: Japanese encephalitis; contextual risk factors; meteorological factors; southwest China; Bayesian hierarchical model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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