Literature DB >> 22855772

Application of an autoregressive integrated moving average model for predicting the incidence of hemorrhagic fever with renal syndrome.

Qi Li1, Na-Na Guo, Zhan-Ying Han, Yan-Bo Zhang, Shun-Xiang Qi, Yong-Gang Xu, Ya-Mei Wei, Xu Han, Ying-Ying Liu.   

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.

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Year:  2012        PMID: 22855772      PMCID: PMC3414578          DOI: 10.4269/ajtmh.2012.11-0472

Source DB:  PubMed          Journal:  Am J Trop Med Hyg        ISSN: 0002-9637            Impact factor:   2.345


  8 in total

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Journal:  Zhonghua Liu Xing Bing Xue Za Zhi       Date:  2004-10

2.  [Applications of multiple seasonal autoregressive integrated moving average (ARIMA) model on predictive incidence of tuberculosis].

Authors:  Jing Yi; Chang-ting Du; Run-hua Wang; Li Liu
Journal:  Zhonghua Yu Fang Yi Xue Za Zhi       Date:  2007-03

3.  Time series analysis of dengue incidence in Rio de Janeiro, Brazil.

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Journal:  Am J Trop Med Hyg       Date:  2008-12       Impact factor: 2.345

4.  Temporal patterns and forecast of dengue infection in Northeastern Thailand.

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5.  [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].

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Journal:  Zhonghua Liu Xing Bing Xue Za Zhi       Date:  1998-04

6.  Influenza and the winter increase in mortality in the United States, 1959-1999.

Authors:  Thomas A Reichert; Lone Simonsen; Ashutosh Sharma; Scott A Pardo; David S Fedson; Mark A Miller
Journal:  Am J Epidemiol       Date:  2004-09-01       Impact factor: 4.897

7.  [The epidemic characteristics and preventive measures of hemorrhagic fever with syndromes in China].

Authors:  Yong-Zhen Zhang; Dong-Lou Xiao; Yu Wang; Hong-Xia Wang; Li Sun; Xiao-Xia Tao; Yong-Gang Qu
Journal:  Zhonghua Liu Xing Bing Xue Za Zhi       Date:  2004-06

8.  Effects of extremely hot days on people older than 65 years in Seville (Spain) from 1986 to 1997.

Authors:  J Díaz; R García; F Velázquez de Castro; E Hernández; C López; A Otero
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  8 in total
  25 in total

1.  A New Hybrid Model Using an Autoregressive Integrated Moving Average and a Generalized Regression Neural Network for the Incidence of Tuberculosis in Heng County, China.

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Journal:  Am J Trop Med Hyg       Date:  2017-08-18       Impact factor: 2.345

2.  Application of seasonal auto-regressive integrated moving average model in forecasting the incidence of hand-foot-mouth disease in Wuhan, China.

Authors:  Ying Peng; Bin Yu; Peng Wang; De-Guang Kong; Bang-Hua Chen; Xiao-Bing Yang
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3.  Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China.

Authors:  Yuhan Xiao; Yanyan Li; Yuhong Li; Chongchong Yu; Yichun Bai; Lei Wang; Yongbin Wang
Journal:  Infect Drug Resist       Date:  2021-09-21       Impact factor: 4.003

4.  Temporal trends and prediction of bovine tuberculosis: a time series analysis in the North-East of Iran.

Authors:  N Esmaeilzadeh; A Bahonar; A Rahimi Foroushani; M Nasehi; K Amiri; M A R Hadjzadeh
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5.  Prediction of Red Blood Cell Demand for Pediatric Patients Using a Time-Series Model: A Single-Center Study in China.

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6.  Time series analysis as a tool to predict the impact of antimicrobial restriction in antibiotic stewardship programs using the example of multidrug-resistant Pseudomonas aeruginosa.

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7.  Comparative study of four time series methods in forecasting typhoid fever incidence in China.

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Journal:  PLoS One       Date:  2013-05-01       Impact factor: 3.240

8.  Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Authors:  K W Wang; C Deng; J P Li; Y Y Zhang; X Y Li; M C Wu
Journal:  Epidemiol Infect       Date:  2017-01-24       Impact factor: 4.434

9.  Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China.

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Journal:  PLoS One       Date:  2015-08-13       Impact factor: 3.240

10.  Establishment and Evaluation of a Time Series Model for Predicting the Seasonality of Acute Upper Gastrointestinal Bleeding.

Authors:  Zhaoli Fu; Xujie Xi; Beiping Zhang; Yanfeng Lin; Aling Wang; Jianmin Li; Ming Luo; Tianwen Liu
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