Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model

BMC Infectious Diseases

Volumn 11, Issue , 2011, Pages

  Liu, Qiyong ^a,b   Liu, Xiaodong ^a,c   Jiang, Baofa ^c   Yang, Weizhong ^d  

^a National Institute for Communicable Disease Control and Prevention   (China)

^b State Key Laboratory for Infectious Disease Prevention and Control   (China)

^c SHANDONG UNIVERSITY   (China)

^d CHINESE CENTER FOR DISEASE CONTROL AND PREVENTION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL PARAMETERS; ARTICLE; AUTOREGRESSIVE INTEGRATED MOVING AVERAGE; CHINA; CONTROLLED STUDY; CORRELATION COEFFICIENT; FORECASTING; HEMORRHAGIC FEVER WITH RENAL SYNDROME; HUMAN; INCIDENCE; MAJOR CLINICAL STUDY; MEAN ABSOLUTE PERCENTAGE ERROR; STOCHASTIC MODEL; TREND STUDY; VALIDITY; METHODOLOGY; STATISTICAL MODEL;

CHINA; FORECASTING; HEMORRHAGIC FEVER WITH RENAL SYNDROME; HUMANS; INCIDENCE; MODELS, STATISTICAL;

EID: 80051582959     PISSN: None     EISSN: 14712334     Source Type: Journal    
DOI: 10.1186/1471-2334-11-218     Document Type: Article

References (33)

1. Fang LQ, Zhao WJ, Vlas SJ, Zhang WY, Liang S, Looman CWN, Yan L, Wang LP, Ma JQ, Feng D, Yang H, Cao WC. Spatiotemporal dynamics of hemorrhagic fever with renal syndrome, Beijing, People's Republic of China. Emerging Infectious Diseases 2009, 15:2043-2045. 3044508, 19961697.
2. Vapalahti K, Paunio M, Brummer-Korvenkontio M, Vaheri A, Vapaahti O. Puumala virus infections in Finland:increased occupational risk for farmers. Am J Epidemiol 1999, 149(12):1142-1151.
3. Glass GE, Childs JE, Korch GW, LeDuc JW. Association of intraspecific wounding with hantaviral infection in wild rats(Rattus norvegicus). Epidemiol Infect 1988, 101:459-472. 10.1017/S0950268800054418, 2249393, 3141203.
4. Zhang YZ, Xiao DL, Wang Y, Wang HX, Sun L, Tao XX, Qu YG. The epidemic characteristics and preventive measures of hemorrhagic fever with renal syndrome in China. Chin J Epidemiol 2004, 25(6):466-469.
5. Ulrich R, Hjelle B, Pitra C, Kuger DH. Emerging viruses: the case 'hantavirus'. Intervirology 2002, 45(4):318-322. 10.1159/000067924, 12602350.
6. Fang LQ, Yan L, Liang S, Vlas SJ, Feng D, Han X, Zhao W, Xu B, Bian L, Yang H, Gong P, Richardus JH, Cao WC. Spatial analysis of hemorrhagic fever with renal syndrome in China. BMC Infect Dis 2006, 6:77. 10.1186/1471-2334-6-77, 1471792, 16638156.
7. Yan L, Fang LQ, Huang HG, Zhang LQ, Feng D, Zhao WJ, Zhang WY, Li XW, Cao WC. Landscape elements and Hantaan virus-related hemorrhagic fever with renal syndrome, People's Republic of China. Emerg Infect Dis 2007, 13(9):1301-1306. 2857277, 18252099.
8. Zhang Y. The epidemiological research status and problems and prospects of hemorrhagic fever with renal syndrome in China. Chin J Vector Bio & Control 2002, 13(2):85-88.
9. Guan P, Huang DS, Zhou BS. Forecasting model for the incidence of hepatitis A based on artificial neural network. World J Gastroenterol 2004, 10(24):3579-3582.
10. Wang YJ, Zhao TQ, Wang P, Li SQ, Huang Z, Yang GQ, Li XY, Liu B. Applying linear regression statistical method to predict the epidemic of hemorrhagic fever with renal syndrome. Chin J Vector Bio & Control 2006, 17(4):333-334.
11. Olsson GE, Hjertqvist M, Lundkvist A, Hornfeldt B. Predicting high risk for human hantavirus infections, Sweden. Emerg Infect Dis 2009, 15(1):104-106. 10.3201/eid1501.080502, 2660694, 19116065.
12. Bi P, Wu XK, Zhang FZ, Parton KA, Tong SL. 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.
13. Clement J, Vercauteren J, Verstraeten WW, Ducoffre G, Barrios JM, Vandamme AM, Maes P, Ranst MV. Relating increasing hantavirus incidences to the changing climate: the mast connection. International J of Health Geographics 2009, 8:1.
14. Guo LC, Wu W, Guo JQ, Wang P, Zhou BS. Appling grey swing model to predict the incidence trend of hemorrhagic fever with renal syndrome in Shenyang. Journal of China Medical University 2008, 37(6):839-842.
15. Wu ZM, Wu W, Wang P, Zhou BS. Prediction for incidence of hemorrhagic fever with renal syndrome with back propagation artificial neural network model. Chin J Vector Bio & Control 2006, 17(3):223-226.
16. Reichert TA, Simonsen L, Sharma A, Pardo SA, Fedson DS, Miller MA. Influenza and the winter increase in mortality in the United States, 1959-1999. Am J Epidemiol 2004, 160(5):492-502. 10.1093/aje/kwh227, 15321847.
17. Gaudart J, Toure O, Dessay N, Dicko AL, Ranque S, Forest L, Demongeot J, Doumbo OK. Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali. Malaria Journal 2009, 8:61. 10.1186/1475-2875-8-61, 2686729, 19361335.
18. Luz PM, Mendes BV, Codeco CT, Struchiner CJ, Galvani AP. Time series analysis of dengue incidence in Rio de Janeiro, Brazil. Am J Trop Med Hyg 2008, 79(6):933-939.
19. Yi J, Du CT, Wang RH, Liu L. Applications of multiple seasonal autoregressive integrated moving average(ARIMA) model on predictive incidence of tuberculosis. Chinese Journal of Preventive Medicine 2007, 41(2):118-121.
20. Box GEP, Jenkins GM. Time series analysis: forecasting and control. 1976, 181-218. San Francisco: Holden Day.
21. Akhtar S, Rozi S. An autoregressive integrated moving average model for short-term prediction of hepatitis C virus seropositivity among male volunteer blood donors in Karachi, Pakistan. World J Gastroenterol 2009, 15(13):1607-1612. 10.3748/wjg.15.1607, 2669945, 19340903.
22. Kuhn L, Davidson LL, Durkin MS. Use of poisson regression and time series analysis for detecting changes over time in rates of child injury following a prevention program. Am J Epidemiol 1994, 140(10):943-955.
23. Wong J, Chan A, Chiang YH. Time series forecasts of the construction labour market in Hong Kong: the Box-Jenkins approach. Construction Management and Economics 2005, 23(9):979-991.
24. Allard R. Use of time-series analysis in infectious disease surveillance. Bulletin of the World Health Organization 1998, 76(4):327-333. 2305771, 9803583.
25. Wang XF, Wang MW, Sun H. Epidemiological analysis of hemorrhagic fever with renal syndrome in China from 2004 to 2005. Disease Surveillance 2007, 22(5):307-309.
26. Bi P, Tong SL, Donald K, Parton K, Ni JF. Climatic, reservoir and occupational variables and the transmission of hemorrhagic fever with renal syndrome in China. Int J of Epidemiol 2002, 31:189-193.
27. Clement J, Vercauteren J, Verstraeten WW, Ducoffre G, Barrios JM, Vandamme AM, Maes P, Ranst MV. Relating increasing hantavirus incidences to the changing climate: the mast connection. International Journal of Health Geographics 2009, 8:1. 10.1186/1476-072X-8-1, 2642778, 19149870.
28. Earnest A, Chen MI, Ng D, Leo YS. Using autoregressive integrated moving average(ARIMA) models to predict and monitor the number of beds occupied during a SARS outbreak in a tertiary hospital in Singapore. BMC Health Services Research 2005, 5:36. 10.1186/1472-6963-5-36, 1274243, 15885149.
29. Li XJ, Kang DM, Cao J, Wang JZ. A time series model in incidence forecasting of hemorrhagic fever with renal syndrome. Journal of Shandong University (Health Sciences) 2008, 46(5):547-549.
30. Wu W, Guan P, Guo JQ, Zhou BS. Comparison of GM(1,1) gray model and ARIMA model in forecasting the incidence of hemorrhagic fever with renal syndrome. Journal of China Medical University 2008, 37(1):52-55.
31. Chen Y, Bai S, Chen HZ, Sun BJ, Wei WJ, Huang M, Wang P. Fitting research on ARMA model in the prediction of incidence trend of hemorrhagic fever with renal syndrome. Modern Preventive Medicine 2008, 35(8):1414-1415.
32. Gao HX compilation SAS System·SAS/ETS Software Manual. 83. Beijing: China Statistics Press, Gao HX compilation.
33. Chen HX, Luo CW. Surveillance of hemorrhagic fever with renal syndrome in China. Chin J Epedimiol 2002, 23(1):63-66.