[1] Schmaljohn C, Hjelle B. Hantaviruses: a global disease problem. Emerg Infect Dis, 1997; 3, 95−104. doi:  10.3201/eid0302.970202
[2] Jonsson CB, Figueiredo LTM, Vapalahti O. A global perspective on Hantavirus ecology, epidemiology, and disease. Clin Microbiol Rev, 2010; 23, 412−41. doi:  10.1128/CMR.00062-09
[3] Avšič-Županc T, Saksida A, Korva M. Hantavirus infections. Clin Microbiolo Infect, 2019; 21, e6−16. doi:  10.1111/1469-0691.12291
[4] Kariwa H, Yoshimatsu K, Arikawa J. Hantavirus infection in East Asia. Comp Immunol Microbiol Infect Dis, 2007; 30, 341−56. doi:  10.1016/j.cimid.2007.05.011
[5] Zhang YZ, Zou Y, Fu ZF, et al. Hantavirus infections in humans and animals, China. Emerg Infect Dis, 2010; 16, 1195−203. doi:  10.3201/eid1608.090470
[6] Zhang WY, Wang LY, Liu YX, et al. Spatiotemporal transmission dynamics of hemorrhagic fever with renal syndrome in China, 2005-2012. PLoS Negl Trop Dis, 2014; 8, e3344. doi:  10.1371/journal.pntd.0003344
[7] Liang WF, Gu X, Li X, et al. Mapping the epidemic changes and risks of hemorrhagic fever with renal syndrome in Shaanxi Province, China, 2005-2016. Sci Rep, 2018; 8, 749. doi:  10.1038/s41598-017-18819-4
[8] Tan X, Xiao D. Epidemic of hemorrhagic fever with renal syndrome and its relationship with rodents in Huxian County, Shaanxi province, China from 2009 to 2012. Chin J Vector Biol Control, 2014; 25, 320−2. (In Chinese
[9] Li Q, Liu JF, Yu LF, et al. Analysis on epidemic characteristics of hemorrhagic fever with renal syndrome. J Med Pest Control, 2016; 32, 850−3. (In Chinese
[10] Bai ZD, Ao Y, Jiang LF, et al. Spatial temporal evolution of land use in Guanzhong Plain urban agglomeration based on GIS. Henan Sci Technol, 2012; 40, 89−92. (In Chinese
[11] Xiao H, Lin XL, Gao LD, et al. Environmental factors contributing to the spread of hemorrhagic fever with renal syndrome and potential risk areas prediction in midstream and downstream of the Xiangjiang River. Sci Geograph Sin, 2013; 33, 123−8. (In Chinese
[12] Tian HY, Stenseth NC. The ecological dynamics of Hantavirus diseases: from environmental variability to disease prevention largely based on data from China. PLoS Negl Trop Dis, 2019; 13, e0006901. doi:  10.1371/journal.pntd.0006901
[13] Xiao D, Wu KJ, Tan X, et al. Modeling and predicting hemorrhagic fever with renal syndrome trends based on meteorological factors in Hu County, China. PLoS One, 2015; 10, e0123166. doi:  10.1371/journal.pone.0123166
[14] Sun MH, Shen L, Gao BX, et al. Factors affecting the incidence of HFRS based on GTWR model in Shaanxi Province. Mod Prev Med, 2020; 47, 4230−4,4280. (In Chinese
[15] Zheng Y, Zhou BY, Wei J, et al. HFRS IgG antibodies in previous HFRS-cases and Vaccinees in Shaanxi province. Mod Prev Med, 2020; 47, 3630−3. (In Chinese
[16] Tian HY, Yu PB, Cazelles B, et al. Interannual cycles of Hantaan virus outbreaks at the human-animal interface in central China are controlled by temperature and rainfall. Proc Natl Acad Sci USA, 2017; 114, 8041−6. doi:  10.1073/pnas.1701777114
[17] Tian HY, Yu PB, Luis AD, et al. Changes in rodent abundance and weather conditions potentially drive hemorrhagic fever with renal syndrome outbreaks in Xi'an, China, 2005-2012. PLoS Negl Trop Dis, 2015; 9, e0003530. doi:  10.1371/journal.pntd.0003530
[18] Zhu LL, Ren HY, Ding F, et al. Spatiotemporal variations and influencing factors of hemorrhagic fever with renal syndrome in Shaanxi Province. J Geo-Inf Sci, 2020; 22, 1142−52. (In Chinese
[19] Yan L, Huang HG, Zhang WY, et al. The relationship between hemorrhagic fever with renal syndrome cases and time series of NDVI in Dayangshu District. J Remote Sens, 2009; 13, 873−86. (In Chinese
[20] Yan L, Fang LQ, Huang HG, et al. Landscape elements and Hantaan virus–related hemorrhagic fever with renal syndrome, People’s Republic of China. Emerg Infect Dis, 2007; 13, 1301−6. doi:  10.3201/eid1309.061481
[21] Li FY, Liu JL, Liu MN, et al. Evaluation on immune effect of Bivalent Vaccine of hemorrhagic fever with renal syndrome in Xianyang, Shaanxi, 2009-2013. Dis Surveill, 2014; 29, 969−72. (In Chinese
[22] Li QX, Ren HY, Zheng L, et al. Ecological niche modeling identifies fine-scale areas at high risk of dengue fever in the Pearl River delta, China. Int J Environ Res Public Health, 2017; 14, 619. doi:  10.3390/ijerph14060619
[23] Xu M, Cao CX, Wang DC, et al. District prediction of cholera risk in China based on environmental factors. Chin Sci Bull, 2013; 58, 2798−804. doi:  10.1007/s11434-013-5776-4
[24] Liu J, Xue FZ, Wang JZ, et al. Association of haemorrhagic fever with renal syndrome and weather factors in Junan County, China: a case-crossover study. Epidemiol Infect, 2013; 141, 697−705. doi:  10.1017/S0950268812001434
[25] Wu J, Wang DD, Li XL, et al. Increasing incidence of hemorrhagic fever with renal syndrome could be associated with livestock husbandry in Changchun, Northeastern China. BMC Infect Dis, 2014; 14, 301. doi:  10.1186/1471-2334-14-301
[26] Fang LQ, Wang XJ, Liang S, et al. Spatiotemporal trends and climatic factors of hemorrhagic fever with renal syndrome epidemic in Shandong Province, China. PLoS Negl Trop Dis, 2010; 4, e789. doi:  10.1371/journal.pntd.0000789
[27] Zhu N, Liu F, Qiu L, et al. Temporal-spatial clustering of hemorrhagic fever with renalsyndrome in Shanxi Province, 2011-2015. Mod Prev Med, 2017; 44, 1537−40,1552. (In Chinese
[28] Statistical Bureau of Shaanxi Province, Shaanxi Survey Team of National Bureau of Statistics. Shanxi statistical yearbook 2016. China Statistical Press. 2016. (In Chinese)
[29] Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions. Ecol Modell, 2006; 190, 231−59. doi:  10.1016/j.ecolmodel.2005.03.026
[30] Phillips SJ, Dudík M, Schapire RE. A maximum entropy approach to species distribution modeling. In: Proceedings of the Twenty-First International Conference on Machine Learning. ACM. 2004.
[31] Elith J, Phillips SJ, Hastie T, et al. A statistical explanation of MaxEnt for ecologists. Divers Distrib, 2011; 17, 43−57. doi:  10.1111/j.1472-4642.2010.00725.x
[32] Merow C, Smith MJ, Silander JA. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography, 2013; 36, 1058−69. doi:  10.1111/j.1600-0587.2013.07872.x
[33] Wang YS, Xie BY, Wan FH, et al. Application of ROC curve analysis in evaluating the performance of alien species' potential distribution models. Biodiversity Sci, 2007; 15, 365−72. (In Chinese doi:  10.1360/biodiv.060280
[34] Greiner M, Pfeiffer D, Smith RD. Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Prev Vet Med, 2000; 45, 23−41. doi:  10.1016/S0167-5877(00)00115-X
[35] Swets JA. Measuring the accuracy of diagnostic systems. Science, 1988; 240, 1285−93. doi:  10.1126/science.3287615
[36] Vanagas G. Receiver operating characteristic curves and comparison of cardiac surgery risk stratification systems. Interact Cardiovasc Thorac Surg, 2004; 3, 319−22. doi:  10.1016/j.icvts.2004.01.008
[37] Sun YF, Hu K, Wu YP, et al. Study on genotype and gene sequence characters of Hantavirus in Baoji. Occup Health, 2016; 32, 1049−52. (In Chinese
[38] Zheng Y, Zhou BY, Zhu N, et al. Epidemiological characteristics and the strategy of vaccination on hemorrhagic fever with renal syndrome in Shaanxi Province, from 2006 to 2017. Chin J Dis Control Prev, 2018; 22, 1073−75. (In Chinese
[39] Wei J, Huang XX, Li S, et al. A total of 2, 657 reported cases and 14 deaths due to hemorrhagic fever with renal syndrome - Shaanxi Province, China, January 1-December 19, 2021. China CDC Wkly, 2021; 3, 1143. doi:  10.46234/ccdcw2021.272
[40] Hassell JM, Begon M, Ward MJ, et al. Urbanization and disease emergence: dynamics at the wildlife-livestock-human interface. Trends Ecol Evol, 2016; 32, 55−67.
[41] Lei XY, Jie ST, Yang H. The formation and evolution of the basin-type Foci of epidemic hemorrhagic fever in Xi'an area. Chin J Zoonoses, 2010; 26, 792−3. (In Chinese
[42] Bao YX. Study on ecology of small mammals in cities under routine rat-killing. Urban Environ Urban Ecol, 2001; 14, 31−3. (In Chinese
[43] Xiao H, Liu HN, Gao LD, et al. Investigating the effects of food available and climatic variables on the animal host density of hemorrhagic fever with renal syndrome in Changsha, China. PLoS One, 2013; 8, e61536. doi:  10.1371/journal.pone.0061536
[44] Tian HY, Hu SX, Cazelles B, et al. Urbanization prolongs hantavirus epidemics in cities. Proc Natl Acad Sci USA, 2018; 115, 4707−12. doi:  10.1073/pnas.1712767115