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DOI:	10.1371/journal.pone.0106839
论文题名:	Time-Specific Ecologic Niche Models Forecast the Risk of Hemorrhagic Fever with Renal Syndrome in Dongting Lake District, China, 2005–2010
作者:	Hai-Ning Liu; Li-Dong Gao; Gerardo Chowell; Shi-Xiong Hu; Xiao-Ling Lin; Xiu-Jun Li; Gui-Hua Ma; Ru Huang; Hui-Suo Yang; Huaiyu Tian; Hong Xiao
刊名:	PLOS ONE
ISSN:	1932-6203
出版年:	2014
发表日期:	2014-9-3
卷:	9, 期:9
语种:	英语
英文关键词:	Hemorrhagic fever with renal syndrome ; Lakes ; Rodents ; Land use ; China ; Ecological niches ; Infectious disease control ; Spring
英文摘要:	Background Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease, is one of the most serious public health threats in China. Increasing our understanding of the spatial and temporal patterns of HFRS infections could guide local prevention and control strategies. Methodology/Principal Findings We employed statistical models to analyze HFRS case data together with environmental data from the Dongting Lake district during 2005–2010. Specifically, time-specific ecologic niche models (ENMs) were used to quantify and identify risk factors associated with HFRS transmission as well as forecast seasonal variation in risk across geographic areas. Results showed that the Maximum Entropy model provided the best predictive ability (AUC = 0.755). Time-specific Maximum Entropy models showed that the potential risk areas of HFRS significantly varied across seasons. High-risk areas were mainly found in the southeastern and southwestern areas of the Dongting Lake district. Our findings based on models focused on the spring and winter seasons showed particularly good performance. The potential risk areas were smaller in March, May and August compared with those identified for June, July and October to December. Both normalized difference vegetation index (NDVI) and land use types were found to be the dominant risk factors. Conclusions/Significance Our findings indicate that time-specific ENMs provide a useful tool to forecast the spatial and temporal risk of HFRS.
URL:	http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0106839&type=printable
Citation statistics:	被引频次[WOS]:32 [查看WOS记录] [查看WOS中相关记录]
资源类型:	期刊论文
标识符:	http://119.78.100.158/handle/2HF3EXSE/18062
Appears in Collections:	过去全球变化的重建影响、适应和脆弱性科学计划与规划气候变化与战略全球变化的国际研究计划气候减缓与适应气候变化事实与影响

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作者单位:

College of Resources and Environment Science, Hunan Normal University, Changsha, China;Hunan Provincial Center for Disease Control and Prevention, Changsha, China;Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America;Simon A. Levin Mathematical, Computational & Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America;Hunan Provincial Center for Disease Control and Prevention, Changsha, China;College of Resources and Environment Science, Hunan Normal University, Changsha, China;School of Public Health, Shandong University, Jinan, China;College of Resources and Environment Science, Hunan Normal University, Changsha, China;College of Resources and Environment Science, Hunan Normal University, Changsha, China;Center for Disease Control and Prevention of Beijing Military Region, Beijing, China;College of Resources and Environment Science, Hunan Normal University, Changsha, China;College of Resources and Environment Science, Hunan Normal University, Changsha, China

Recommended Citation:

Hai-Ning Liu,Li-Dong Gao,Gerardo Chowell,et al. Time-Specific Ecologic Niche Models Forecast the Risk of Hemorrhagic Fever with Renal Syndrome in Dongting Lake District, China, 2005–2010[J]. PLOS ONE,2014-01-01,9(9)

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