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Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in mainland China. HFRS is particularly endemic in Changsha, the capital city of Hunan Province, with one of the highest incidences in China. The occurrence of HFRS is influenced by environmental factors....

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Autores principales: Xiao, Hong, Lin, Xiaoling, Gao, Lidong, Huang, Cunrui, Tian, Huaiyu, Li, Na, Qin, Jianxin, Zhu, Peijuan, Chen, Biyun, Zhang, Xixing, Zhao, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708768/
https://www.ncbi.nlm.nih.gov/pubmed/23819824
http://dx.doi.org/10.1186/1471-2334-13-305
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author Xiao, Hong
Lin, Xiaoling
Gao, Lidong
Huang, Cunrui
Tian, Huaiyu
Li, Na
Qin, Jianxin
Zhu, Peijuan
Chen, Biyun
Zhang, Xixing
Zhao, Jian
author_facet Xiao, Hong
Lin, Xiaoling
Gao, Lidong
Huang, Cunrui
Tian, Huaiyu
Li, Na
Qin, Jianxin
Zhu, Peijuan
Chen, Biyun
Zhang, Xixing
Zhao, Jian
author_sort Xiao, Hong
collection PubMed
description BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in mainland China. HFRS is particularly endemic in Changsha, the capital city of Hunan Province, with one of the highest incidences in China. The occurrence of HFRS is influenced by environmental factors. However, few studies have examined the relationship between environmental variation (such as land use changes and climate variations), rodents and HFRS occurrence. The purpose of this study is to predict the distribution of HFRS and identify the risk factors and relationship between HFRS occurrence and rodent hosts, combining ecological modeling with the Markov chain Monte Carlo approach. METHODS: Ecological niche models (ENMs) were used to evaluate potential geographic distributions of rodent species by reconstructing details of their ecological niches in ecological dimensions, and projecting the results onto geography. The Genetic Algorithm for Rule-set Production was used to produce ENMs. Data were collected on HFRS cases in Changsha from 2005 to 2009, as well as national land survey data, surveillance data of rodents, meteorological data and normalized difference vegetation index (NDVI). RESULTS: The highest occurrence of HFRS was in districts with strong temperature seasonality, where elevation is below 200 m, mean annual temperature is around 17.5°C, and annual precipitation is below 1600 mm. Cultivated and urban lands in particular are associated with HFRS occurrence. Monthly NDVI values of areas predicted present is lower than areas predicted absent, with high seasonal variation. The number of HFRS cases was correlated with rodent density, and the incidence of HFRS cases in urban and forest areas was mainly associated with the density of Rattus norvegicus and Apodemus agrarius, respectively. CONCLUSIONS: Heterogeneity between different areas shows that HFRS occurrence is affected by the intensity of human activity, climate conditions, and landscape elements. Rodent density and species composition have significant impacts on the number of HFRS cases and their distribution.
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spelling pubmed-37087682013-07-15 Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China Xiao, Hong Lin, Xiaoling Gao, Lidong Huang, Cunrui Tian, Huaiyu Li, Na Qin, Jianxin Zhu, Peijuan Chen, Biyun Zhang, Xixing Zhao, Jian BMC Infect Dis Research Article BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in mainland China. HFRS is particularly endemic in Changsha, the capital city of Hunan Province, with one of the highest incidences in China. The occurrence of HFRS is influenced by environmental factors. However, few studies have examined the relationship between environmental variation (such as land use changes and climate variations), rodents and HFRS occurrence. The purpose of this study is to predict the distribution of HFRS and identify the risk factors and relationship between HFRS occurrence and rodent hosts, combining ecological modeling with the Markov chain Monte Carlo approach. METHODS: Ecological niche models (ENMs) were used to evaluate potential geographic distributions of rodent species by reconstructing details of their ecological niches in ecological dimensions, and projecting the results onto geography. The Genetic Algorithm for Rule-set Production was used to produce ENMs. Data were collected on HFRS cases in Changsha from 2005 to 2009, as well as national land survey data, surveillance data of rodents, meteorological data and normalized difference vegetation index (NDVI). RESULTS: The highest occurrence of HFRS was in districts with strong temperature seasonality, where elevation is below 200 m, mean annual temperature is around 17.5°C, and annual precipitation is below 1600 mm. Cultivated and urban lands in particular are associated with HFRS occurrence. Monthly NDVI values of areas predicted present is lower than areas predicted absent, with high seasonal variation. The number of HFRS cases was correlated with rodent density, and the incidence of HFRS cases in urban and forest areas was mainly associated with the density of Rattus norvegicus and Apodemus agrarius, respectively. CONCLUSIONS: Heterogeneity between different areas shows that HFRS occurrence is affected by the intensity of human activity, climate conditions, and landscape elements. Rodent density and species composition have significant impacts on the number of HFRS cases and their distribution. BioMed Central 2013-07-03 /pmc/articles/PMC3708768/ /pubmed/23819824 http://dx.doi.org/10.1186/1471-2334-13-305 Text en Copyright © 2013 Xiao et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Xiao, Hong
Lin, Xiaoling
Gao, Lidong
Huang, Cunrui
Tian, Huaiyu
Li, Na
Qin, Jianxin
Zhu, Peijuan
Chen, Biyun
Zhang, Xixing
Zhao, Jian
Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China
title Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China
title_full Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China
title_fullStr Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China
title_full_unstemmed Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China
title_short Ecology and geography of hemorrhagic fever with renal syndrome in Changsha, China
title_sort ecology and geography of hemorrhagic fever with renal syndrome in changsha, china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708768/
https://www.ncbi.nlm.nih.gov/pubmed/23819824
http://dx.doi.org/10.1186/1471-2334-13-305
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