Exploring the Dynamics of Hemorrhagic Fever with Renal Syndrome Incidence in East China Through Seasonal Autoregressive Integrated Moving Average Models

References

• Jonsson CB, Figueiredo LT, Vapalahti O. A global perspective on hantavirus ecology, epidemiology, and disease. Clin Microbiol Rev. 2010;23(2):412–441. doi:10.1128/CMR.00062-0920375360
   PubMed Web of Science ®Google Scholar
• Vaheri A, Strandin T, Hepojoki J, et al. Uncovering the mysteries of hantavirus infections. Nat Rev Microbiol. 2013;11(8):539–550. doi:10.1038/nrmicro306624020072
   PubMed Web of Science ®Google Scholar
• Lei Yan L-QF, Hua-Guo H, Long-Qi Z, et al. Landscape elements and hantaan virus–related hemorrhagic fever with renal syndrome, People’s Republic of China. Emerg Infect Dis. 2007;13(9):1301–1306. doi:10.3201/eid1309.06148118252099
   PubMed Web of Science ®Google Scholar
• Shuo Zhang SW, Yin W, Liang M, et al. Epidemic characteristics of hemorrhagic fever with renal syndrome in China, 2006-2012. BMC Infect Dis Vol. 2014;14:384. doi:10.1186/1471-2334-14-384
   Web of Science ®Google Scholar
• Wang L, Wang T, Cui F, et al. Hemorrhagic fever with renal syndrome, Zibo City, China, 2006–2014. Emerg Infect Dis. 2016;22(2):274–276. doi:10.3201/eid2202.15151626812444
   PubMed Web of Science ®Google Scholar
• Wang T, Liu J, Zhou Y, et al. Prevalence of hemorrhagic fever with renal syndrome in Yiyuan County, China, 2005-2014. BMC Infect Dis. 2016;16:69. doi:10.1186/s12879-016-1404-726852019
   PubMed Web of Science ®Google Scholar
• Seung Seok Han SK, Choi Y, Kim S, Su Kim Y. Air pollution and hemorrhagic fever with renal syndrome in South Korea_ an ecological correlation study. BMC Public Health. 2013;13:347. doi:10.1186/1471-2458-13-34723587219
   PubMed Web of Science ®Google Scholar
• Hualiang Lin ZZ, Liang L, Xiujun L, Liu Q. Meteorological factors are associated with hemorrhagic fever with renal syndrome in Jiaonan County, China, 2006–2011. Int J Biometeorol. 2014;58(6):1031–1037. doi:10.1007/s00484-013-0688-123793957
   PubMed Web of Science ®Google Scholar
• Wu W, Guo J, An S, et al. Comparison of two hybrid models for forecasting the incidence of hemorrhagic fever with renal syndrome in Jiangsu Province, China. PLoS One. 2015;10(8):e0135492. doi:10.1371/journal.pone.013549226270814
   PubMed Web of Science ®Google Scholar
• Peng Bi XW, Fangzhen Zhang KA, Parton ST. Seasonal rainfall variability, the incidence of hemorrhagic fever with renal syndrome, and prediction of the disease in low-lying areas of China. Am J Epidemiol. 1998;148(3):276–281. doi:10.1093/oxfordjournals.aje.a0096369690365
   PubMed Web of Science ®Google Scholar
• Olsson GE, Hjertqvist M, Lundkvist A, Hornfeldt B. Predicting high risk for human hantavirus infections, Sweden. Emerg Infect Dis. 2009;15(1):104–106. doi:10.3201/eid1501.08050219116065
   PubMed Web of Science ®Google Scholar
• Wei Y, Wang Y, Li X, et al. Meteorological factors and risk of hemorrhagic fever with renal syndrome in Guangzhou, southern China, 2006-2015. PLoS Negl Trop Dis. 2018;12(6):e0006604. doi:10.1371/journal.pntd.000660429949572
   PubMed Web of Science ®Google Scholar
• Jiang F, Wang L, Wang S, et al. Meteorological factors affect the epidemiology of hemorrhagic fever with renal syndrome via altering the breeding and hantavirus-carrying states of rodents and mites: a 9 years’ longitudinal study. Emerg Microbes Infect. 2017;6(11):e104. doi:10.1038/emi.2017.9229184158
   PubMed Web of Science ®Google Scholar
• Wen-Yi Zhang W-DG, Fang L-Q, Chang-Ping L, et al. Climate variability and hemorrhagic fever with renal syndrome transmission in Northeastern China. Environ Health Perspect. 2010;118(7):915–920. doi:10.1289/ehp.090150420142167
   PubMed Web of Science ®Google Scholar
• Qiyong Liu XL, Jiang B, Yang W. Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model. BMC Infect Dis. 2011;11:218. doi:10.1186/1471-2334-11-21821838933
   PubMed Web of Science ®Google Scholar
• Wang T, Zhou Y, Wang L, Huang Z, Cui F, Zhai S. Using an autoregressive integrated moving average model to predict the incidence of hemorrhagic fever with renal syndrome in Zibo, China, 2004–2014. Jpn J Infect Dis. 2016;69(4):279–284. doi:10.7883/yoken.JJID.2014.56726370428
   PubMed Web of Science ®Google Scholar
• Xiao DW, Tan K, Le X, Li J, Yan H, Xu Y. Modeling and predicting hemorrhagic fever with renal syndrome trends based on meteorological factors in Hu County, China. PLoS One. 2015;10(4):e0123166. doi:10.1371/journal.pone.012316625875211
   PubMed Web of Science ®Google Scholar
• Zheng YL, Zhang LP, Zhang XL, Wang K, Zheng YJ. Forecast model analysis for the morbidity of tuberculosis in Xinjiang, China. PLoS One. 2015;10(3):e0116832. doi:10.1371/journal.pone.011683225760345
   PubMed Web of Science ®Google Scholar
• Wongkoon S, Jaroensutasinee M, Jaroensutasinee K. Development of temporal modeling for prediction of dengue infection in Northeastern Thailand. Asian Pac J Trop Med. 2012;5(3):249–252. doi:10.1016/S1995-7645(12)60034-022305794
   PubMed Web of Science ®Google Scholar
• Liu L, Luan RS, Yin F, Zhu XP, Lu Q. Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model. Epidemiol Infect. 2016;144(1):144–151. doi:10.1017/S095026881500114426027606
   PubMed Web of Science ®Google Scholar
• Wen-Yi Zhang L-QF, Jiang J-F, Feng-Ming Hui GE, et al. Predicting the risk of hantavirus infection in Beijing, People’s Republic of China. Am J Trop Med Hyg. 2009;80(4):678–683. doi:10.4269/ajtmh.2009.80.67819346399
   PubMed Web of Science ®Google Scholar
• Xiang J, Hansen A, Liu Q, et al. Impact of meteorological factors on hemorrhagic fever with renal syndrome in 19 cities in China, 2005–2014. Sci Total Environ. 2018;636:1249–1256. doi:10.1016/j.scitotenv.2018.04.40729913587
   PubMed Web of Science ®Google Scholar
• 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(8):e789. doi:10.1371/journal.pntd.000078920706629
   PubMed Web of Science ®Google Scholar
• Box GJ, Reinsel GC, Ljung GM. Time Series Analysis: Forecasting and Control. 2015.
   Google Scholar
• Ho SL, X M, Goh TN. A comparative study of neural network and Box-Jenkins ARIMA modeling in time series prediction. Comp Ind Eng. 2002;42(2–4):371–375. doi:10.1016/S0360-8352(02)00036-0
   Web of Science ®Google Scholar
• Gerolimetto SM. On the power of the simulation-based ADF test in bounded time series. Econ Bull. 2017;37(1):539–552.
   Google Scholar
• Galbraith JW, W VZ. On the distributions of Augmented Dickey–Fuller statistics in processes with moving average components. J Econom. 1999;93(1):25–47. doi:10.1016/S0304-4076(98)00097-9
   Web of Science ®Google Scholar
• Ljung GM, Box GEP. On a measure of lack of fit in time series models. Biometrika. 1978;65(2):297–334. doi:10.1093/biomet/65.2.297
   Web of Science ®Google Scholar
• Allard R. Use of time-series analysis in infectious disease surveillance. Bull World Health Organ. 1998;76(4):327–333.9803583
   PubMed Web of Science ®Google Scholar
• Bai Y, Xu Z, Lu B, et al. Effects of climate and rodent factors on hemorrhagic fever with renal syndrome in Chongqing, China, 1997–2008. PLoS One. 2015;10(7):e0133218. doi:10.1371/journal.pone.013321826193359
   PubMed Web of Science ®Google Scholar
• Guan P, Huang D, He M, Shen T, Guo J, Zhou B. Investigating the effects of climatic variables and reservoir on the incidence of hemorrhagic fever with renal syndrome in Huludao City, China: a 17-year data analysis based on structure equation model. BMC Infect Dis. 2009;9:109. doi:10.1186/1471-2334-9-10919583875
   PubMed Web of Science ®Google Scholar
• Bi P, Donald K, Parton K, Jinfa N. Climatic, reservoir and occupational variables and the transmission of haemorrhagic fever with renal syndrome in China. Int J Epidemiol. 2002;31(1):189–193. doi:10.1093/ije/31.1.18911914320
   PubMed Web of Science ®Google Scholar
• Xiaodong Liu BJ, Weidong G, Liu Q. Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China. BMC Infect Dis. 2011;11:331. doi:10.1186/1471-2334-11-33122133347
   PubMed Web of Science ®Google Scholar
• David M, Engelthaler DGM, Cheek JE, et al. Climatic and environmental patterns associated with hantavirus pulmonary syndrome, Four Corners region, United States. Emerg Infect Dis. 1999;5(1):87–94. doi:10.3201/eid0501.99011010081675
   PubMed Web of Science ®Google Scholar
• Tamerius JD, Wise EK, Uejio CK, McCoy AL, Comrie AC. Climate and human health: synthesizing environmental complexity and uncertainty. Stochastic Environ Res Risk Assess. 2007;21(5):601–613. doi:10.1007/s00477-007-0142-1
   Web of Science ®Google Scholar
• Brian Hjelle GEG. Outbreak of hantavirus infection in the four corners region of the United States in the wake of the 1997-1998 El Nino-southern oscillation. J Infect Dis. 2000;181(5):1569–1573. doi:10.1086/31546710823755
   PubMed Web of Science ®Google Scholar
• Tian H-Y, Yu P-B, 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(3):e0003530. doi:10.1371/journal.pntd.000353025822936
   PubMed Web of Science ®Google Scholar
• Duan Y, Huang XL, Wang YJ, et al. Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China. Int J Biometeorol. 2016;60(10):1543–1550. doi:10.1007/s00484-016-1145-826932715
   PubMed Web of Science ®Google Scholar
• Puca EQM, Pipero P, Akshija I, Kote M, Kraja D. Two cases of imported hemorrhagic fever with renal syndrome and systematic review of literature. Travel Med Infect Dis. 2019;28:86–90. doi:10.1016/j.tmaid.2018.07.01030114480
   PubMed Web of Science ®Google Scholar