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Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013

BACKGROUND: Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology...

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Autores principales: Chen, Yan-Yan, Huang, Xi-Bao, Xiao, Ying, Jiang, Yong, Shan, Xiao-wei, Zhang, Juan, Cai, Shun-Xiang, Liu, Jian-Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388649/
https://www.ncbi.nlm.nih.gov/pubmed/25849567
http://dx.doi.org/10.1371/journal.pone.0118362
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author Chen, Yan-Yan
Huang, Xi-Bao
Xiao, Ying
Jiang, Yong
Shan, Xiao-wei
Zhang, Juan
Cai, Shun-Xiang
Liu, Jian-Bing
author_facet Chen, Yan-Yan
Huang, Xi-Bao
Xiao, Ying
Jiang, Yong
Shan, Xiao-wei
Zhang, Juan
Cai, Shun-Xiang
Liu, Jian-Bing
author_sort Chen, Yan-Yan
collection PubMed
description BACKGROUND: Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions. METHODS: In this study, spatial autocorrelation methodologies, including global Moran’s I and local Getis–Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time. RESULTS: The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran’s I > 0, P < 0.01), which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties. CONCLUSIONS: The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial–temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be continued, especially in the Yangtze River Basin of Jianghan Plain area.
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spelling pubmed-43886492015-04-21 Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013 Chen, Yan-Yan Huang, Xi-Bao Xiao, Ying Jiang, Yong Shan, Xiao-wei Zhang, Juan Cai, Shun-Xiang Liu, Jian-Bing PLoS One Research Article BACKGROUND: Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions. METHODS: In this study, spatial autocorrelation methodologies, including global Moran’s I and local Getis–Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time. RESULTS: The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran’s I > 0, P < 0.01), which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties. CONCLUSIONS: The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial–temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be continued, especially in the Yangtze River Basin of Jianghan Plain area. Public Library of Science 2015-04-07 /pmc/articles/PMC4388649/ /pubmed/25849567 http://dx.doi.org/10.1371/journal.pone.0118362 Text en © 2015 Chen et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chen, Yan-Yan
Huang, Xi-Bao
Xiao, Ying
Jiang, Yong
Shan, Xiao-wei
Zhang, Juan
Cai, Shun-Xiang
Liu, Jian-Bing
Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013
title Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013
title_full Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013
title_fullStr Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013
title_full_unstemmed Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013
title_short Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013
title_sort spatial analysis of schistosomiasis in hubei province, china: a gis-based analysis of schistosomiasis from 2009 to 2013
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388649/
https://www.ncbi.nlm.nih.gov/pubmed/25849567
http://dx.doi.org/10.1371/journal.pone.0118362
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