自回归积分滑动平均模型在预测肾综合征出血热发病率中的应用。
Application of an autoregressive integrated moving average model for predicting the incidence of hemorrhagic fever with renal syndrome.
机构信息
Hebei Center for Disease Control and Prevention, Yuhua District, Shijiazhuang, China.
出版信息
Am J Trop Med Hyg. 2012 Aug;87(2):364-70. doi: 10.4269/ajtmh.2012.11-0472.
Abstract
The Box-Jenkins approach was used to fit an autoregressive integrated moving average (ARIMA) model to the incidence of hemorrhagic fever with renal Syndrome (HFRS) in China during 1986-2009. The ARIMA (0, 1, 1) × (2, 1, 0)(12) models fitted exactly with the number of cases during January 1986-December 2009. The fitted model was then used to predict HFRS incidence during 2010, and the number of cases during January-December 2010 fell within the model's confidence interval for the predicted number of cases in 2010. This finding suggests that the ARIMA model fits the fluctuations in HFRS frequency and it can be used for future forecasting when applied to HFRS prevention and control.
摘要
采用 Box-Jenkins 方法，对中国 1986-2009 年肾综合征出血热（HFRS）发病率进行自回归求和移动平均（ARIMA）模型拟合。ARIMA（0,1,1）×（2,1,0）（12）模型与 1986 年 1 月至 2009 年 12 月期间的病例数完全拟合。然后使用拟合模型预测 2010 年 HFRS 发病率，2010 年 1 月至 12 月期间的病例数在该模型对 2010 年预测病例数的置信区间内。这一发现表明，ARIMA 模型适用于 HFRS 发病率的波动，可以用于 HFRS 预防和控制的未来预测。
相似文献
1
Application of an autoregressive integrated moving average model for predicting the incidence of hemorrhagic fever with renal syndrome.
Am J Trop Med Hyg. 2012 Aug;87(2):364-70. doi: 10.4269/ajtmh.2012.11-0472.
2
Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model.
BMC Infect Dis. 2011 Aug 15;11:218. doi: 10.1186/1471-2334-11-218.
3
Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study.
BMJ Open. 2019 Jun 16;9(6):e025773. doi: 10.1136/bmjopen-2018-025773.
4
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 Jul 22;69(4):279-84. doi: 10.7883/yoken.JJID.2014.567. Epub 2015 Sep 11.
5
Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China.
PLoS One. 2015 Aug 13;10(8):e0135492. doi: 10.1371/journal.pone.0135492. eCollection 2015.
6
Prevalence of hemorrhagic fever with renal syndrome in Yiyuan County, China, 2005-2014.
BMC Infect Dis. 2016 Feb 6;16:69. doi: 10.1186/s12879-016-1404-7.
7
Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach.
PLoS One. 2021 Mar 16;16(3):e0248597. doi: 10.1371/journal.pone.0248597. eCollection 2021.
8
Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model.
BMC Infect Dis. 2021 Aug 19;21(1):839. doi: 10.1186/s12879-021-06503-y.
9
[Application of nonlinear autoregressive neural network in predicting incidence tendency of hemorrhagic fever with renal syndrome].
Zhonghua Liu Xing Bing Xue Za Zhi. 2015 Dec;36(12):1394-6.
10
Spatiotemporal analysis and forecasting model of hemorrhagic fever with renal syndrome in mainland China.
Epidemiol Infect. 2018 Oct;146(13):1680-1688. doi: 10.1017/S0950268818002030. Epub 2018 Aug 6.
引用本文的文献
1
Trends, levels, and projections of Head and Neck Cancer in China between 2000 and 2021: Findings from the Global Burden of Disease 2021.
PLoS One. 2025 May 2;20(5):e0322533. doi: 10.1371/journal.pone.0322533. eCollection 2025.
2
The ecological and etiological investigation of ticks and rodents in China: results from an ongoing surveillance study in Zhejiang Province.
Front Vet Sci. 2023 Nov 28;10:1268440. doi: 10.3389/fvets.2023.1268440. eCollection 2023.
3
Temporal trends and prediction of bovine tuberculosis: a time series analysis in the North-East of Iran.
Iran J Vet Res. 2022;23(1):12-17. doi: 10.22099/IJVR.2021.39440.5727.
4
Prediction of Red Blood Cell Demand for Pediatric Patients Using a Time-Series Model: A Single-Center Study in China.
Front Med (Lausanne). 2022 May 19;9:706284. doi: 10.3389/fmed.2022.706284. eCollection 2022.
5
Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost.
PLoS One. 2021 Dec 22;16(12):e0261629. doi: 10.1371/journal.pone.0261629. eCollection 2021.
6
Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China.
Infect Drug Resist. 2021 Sep 21;14:3849-3862. doi: 10.2147/IDR.S325787. eCollection 2021.
7
Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India.
J Biomed Inform. 2021 Sep;121:103887. doi: 10.1016/j.jbi.2021.103887. Epub 2021 Aug 15.
8
Establishment and Evaluation of a Time Series Model for Predicting the Seasonality of Acute Upper Gastrointestinal Bleeding.
Int J Gen Med. 2021 May 26;14:2079-2086. doi: 10.2147/IJGM.S299208. eCollection 2021.
9
COVID-19: Forecasting confirmed cases and deaths with a simple time series model.
Int J Forecast. 2022 Apr-Jun;38(2):439-452. doi: 10.1016/j.ijforecast.2020.11.010. Epub 2020 Dec 4.
10
Modeling the Number of Confirmed Cases and Deaths from the COVID-19 Pandemic in the UK and Forecasting from April 15 to May 30, 2020.
Disaster Med Public Health Prep. 2022 Feb;16(1):187-193. doi: 10.1017/dmp.2020.312. Epub 2020 Sep 3.
本文引用的文献
1
Time series analysis of dengue incidence in Rio de Janeiro, Brazil.
Am J Trop Med Hyg. 2008 Dec;79(6):933-9.
2
Temporal patterns and forecast of dengue infection in Northeastern Thailand.
Southeast Asian J Trop Med Public Health. 2008 Jan;39(1):90-8.
3
[Applications of multiple seasonal autoregressive integrated moving average (ARIMA) model on predictive incidence of tuberculosis].
Zhonghua Yu Fang Yi Xue Za Zhi. 2007 Mar;41(2):118-21.
4
[Application of "time series analysis" in the prediction of schistosomiasis prevalence in areas of "breaking dikes or opening sluice for waterstore" in Dongting Lake areas, China].
Zhonghua Liu Xing Bing Xue Za Zhi. 2004 Oct;25(10):863-6.
5
Influenza and the winter increase in mortality in the United States, 1959-1999.
Am J Epidemiol. 2004 Sep 1;160(5):492-502. doi: 10.1093/aje/kwh227.
6
[The epidemic characteristics and preventive measures of hemorrhagic fever with syndromes in China].
Zhonghua Liu Xing Bing Xue Za Zhi. 2004 Jun;25(6):466-9.
7
Effects of extremely hot days on people older than 65 years in Seville (Spain) from 1986 to 1997.
Int J Biometeorol. 2002 Aug;46(3):145-9. doi: 10.1007/s00484-002-0129-z. Epub 2002 Apr 25.
8
[Application of the time-series method to analyse the seasonal distribution of epidemic encephalitis B incidence in Guangdong province in the years of 1984-1993].
Zhonghua Liu Xing Bing Xue Za Zhi. 1998 Apr;19(2):103-6.
Zotero 插件