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

被引:26
作者
Xiao, Hong [1 ]
Lin, Xiaoling [1 ]
Gao, Lidong [2 ]
Huang, Cunrui [3 ]
Tian, Huaiyu [1 ]
Li, Na [4 ]
Qin, Jianxin [1 ]
Zhu, Peijuan [1 ]
Chen, Biyun [2 ]
Zhang, Xixing [5 ]
Zhao, Jian [6 ]
机构
[1] Hunan Normal Univ, Coll Resources & Environm Sci, Changsha 410081, Hunan, Peoples R China
[2] Hunan Prov Ctr Dis Control & Prevent, Changsha 410002, Hunan, Peoples R China
[3] Griffith Univ, Sch Environm, Ctr Environm & Populat Hlth, Brisbane, Qld 4111, Australia
[4] Sichuan Univ, West China Sch Publ Hlth, Chengdu 610041, Peoples R China
[5] Changsha Municipal Ctr Dis Control & Prevent, Changsha 410001, Hunan, Peoples R China
[6] Peking Univ, Hlth Sci Ctr, Beijing 100191, Peoples R China
关键词
SPECIES DISTRIBUTIONS; SHANDONG PROVINCE; DISEASE; MODELS; VARIABILITY; PREDICTION; EPIDEMIC; SYSTEM; RISK;
D O I
10.1186/1471-2334-13-305
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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 degrees 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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页数:11
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