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

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 repor...

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Autores principales: Zhao, Xing, Cao, Mingqin, Feng, Hai-Huan, Fan, Heng, Chen, Fei, Feng, Zijian, Li, Xiaosong, Zhou, Xiao-Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4024990/
https://www.ncbi.nlm.nih.gov/pubmed/24739769
http://dx.doi.org/10.3390/ijerph110404201
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author Zhao, Xing
Cao, Mingqin
Feng, Hai-Huan
Fan, Heng
Chen, Fei
Feng, Zijian
Li, Xiaosong
Zhou, Xiao-Hua
author_facet Zhao, Xing
Cao, Mingqin
Feng, Hai-Huan
Fan, Heng
Chen, Fei
Feng, Zijian
Li, Xiaosong
Zhou, Xiao-Hua
author_sort Zhao, Xing
collection PubMed
description 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.
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spelling pubmed-40249902014-05-19 Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis Zhao, Xing Cao, Mingqin Feng, Hai-Huan Fan, Heng Chen, Fei Feng, Zijian Li, Xiaosong Zhou, Xiao-Hua Int J Environ Res Public Health Article 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. MDPI 2014-04 2014-04-15 /pmc/articles/PMC4024990/ /pubmed/24739769 http://dx.doi.org/10.3390/ijerph110404201 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Zhao, Xing
Cao, Mingqin
Feng, Hai-Huan
Fan, Heng
Chen, Fei
Feng, Zijian
Li, Xiaosong
Zhou, Xiao-Hua
Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
title Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
title_full Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
title_fullStr Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
title_full_unstemmed Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
title_short Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
title_sort japanese encephalitis risk and contextual risk factors in southwest china: a bayesian hierarchical spatial and spatiotemporal analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4024990/
https://www.ncbi.nlm.nih.gov/pubmed/24739769
http://dx.doi.org/10.3390/ijerph110404201
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