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Infection rates of rodents have a significant influence on the transmission of hemorrhagic fever with renal syndrome (HFRS). In this study, four cities and two counties with high HFRS incidence in eastern Hunan Province in China were studied, and surveillance data of rodents, as well as HFRS cases and related environmental variables from 2007 to 2010, were collected. Results indicate that the distribution and infection rates of rodents are closely associated with environmental conditions. Hantavirus infections in rodents were positively correlated with temperature vegetation dryness index and negatively correlated with elevation. The predictive risk maps based on multivariate regression model revealed that the annual variation of infection risks is small, whereas monthly variation is large and corresponded well to the seasonal variation of human HFRS incidence. The identification of risk factors and risk prediction provides decision support for rodent surveillance and the prevention and control of HFRS.
Financial support: This work was supported by the Key Discipline Construction Project in Hunan Province (2008001), National Natural Science Foundation (40971038), Scientific Research Fund of the Hunan Provincial Education Department (11K037), Hunan Provincial Natural Science Foundation of China (11JJ3119), Science and Technology Planning Project of Hunan Province of China (2010SK3007), and Key Subject Construction Project of Hunan Normal University (geographic information systems).
Authors' addresses: Hong Xiao, Ru Huang, Xiao-Ling Lin, and Hai-Ning Liu, College of Resources and Environment Science, Hunan Normal University, Changsha, China, E-mails: email@example.com, firstname.lastname@example.org, email@example.com, and firstname.lastname@example.org. Li-Dong Gao, Hunan Provincial Center for Disease Control and Prevention, Changsha, China, E-mail: email@example.com. Cun-Rui Huang, School of Public Health, Sun Yat-Sen University, Guangzhou, China, E-mail: firstname.lastname@example.org. Na Li, Weizikeng Center for Disease Control and Prevention, Beijing, China, E-mail: email@example.com. Shi-Lu Tong, School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia, E-mail: firstname.lastname@example.org. Huai-Yu Tian, State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China, E-mail: email@example.com.