Literature DB >> 26027606

Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model.

L Liu1, R S Luan1, F Yin1, X P Zhu2, Q Lü2.   

Abstract

Hand, foot and mouth disease (HFMD) is an infectious disease caused by enteroviruses, which usually occurs in children aged <5 years. In China, the HFMD situation is worsening, with increasing number of cases nationwide. Therefore, monitoring and predicting HFMD incidence are urgently needed to make control measures more effective. In this study, we applied an autoregressive integrated moving average (ARIMA) model to forecast HFMD incidence in Sichuan province, China. HFMD infection data from January 2010 to June 2014 were used to fit the ARIMA model. The coefficient of determination (R 2), normalized Bayesian Information Criterion (BIC) and mean absolute percentage of error (MAPE) were used to evaluate the goodness-of-fit of the constructed models. The fitted ARIMA model was applied to forecast the incidence of HMFD from April to June 2014. The goodness-of-fit test generated the optimum general multiplicative seasonal ARIMA (1,0,1) × (0,1,0)12 model (R 2 = 0·692, MAPE = 15·982, BIC = 5·265), which also showed non-significant autocorrelations in the residuals of the model (P = 0·893). The forecast incidence values of the ARIMA (1,0,1) × (0,1,0)12 model from July to December 2014 were 4103-9987, which were proximate forecasts. The ARIMA model could be applied to forecast HMFD incidence trend and provide support for HMFD prevention and control. Further observations should be carried out continually into the time sequence, and the parameters of the models could be adjusted because HMFD incidence will not be absolutely stationary in the future.

Entities:  

Keywords:  ARIMA; forecasting; hand; foot and mouth disease (HFMD)

Mesh:

Year:  2015        PMID: 26027606      PMCID: PMC9507307          DOI: 10.1017/S0950268815001144

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   4.434


  15 in total

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Journal:  Indian J Community Med       Date:  2014-10

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Authors:  Seong Joon Kim; Jong-Hyun Kim; Jin-Han Kang; Dong Soo Kim; Ki Hwan Kim; Kyung-Hyo Kim; Young-Hoon Kim; Ju-Young Chung; Joong Hyun Bin; Da Eun Jung; Ji Hong Kim; Hwang Min Kim; Doo-Sung Cheon; Byung Hak Kang; Soon Young Seo
Journal:  J Korean Med Sci       Date:  2013-01-08       Impact factor: 2.153

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  28 in total

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

Authors:  Fuyan Shi; Changlan Yu; Liping Yang; Fangyou Li; Jiangtao Lun; Wenfeng Gao; Yongyong Xu; Yufei Xiao; Sravya B Shankara; Qingfeng Zheng; Bo Zhang; Suzhen Wang
Journal:  Infect Drug Resist       Date:  2020-07-21       Impact factor: 4.003

2.  Application of the ARIMA Model in Forecasting the Incidence of Tuberculosis in Anhui During COVID-19 Pandemic from 2021 to 2022.

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Journal:  Infect Drug Resist       Date:  2022-07-04       Impact factor: 4.177

3.  Exploring the influence of COVID-19 on the spread of hand, foot, and mouth disease with an automatic machine learning prediction model.

Authors:  Chuan Yang; Shuyi An; Baojun Qiao; Peng Guan; Desheng Huang; Wei Wu
Journal:  Environ Sci Pollut Res Int       Date:  2022-10-18       Impact factor: 5.190

4.  Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model - CORRIGENDUM.

Authors:  L Liu; R S Luan; F Yin; X P Zhu; Q Lü
Journal:  Epidemiol Infect       Date:  2015-07-06       Impact factor: 4.434

5.  Tracking and predicting hand, foot, and mouth disease (HFMD) epidemics in China by Baidu queries.

Authors:  Q Y Xiao; H J Liu; M W Feldman
Journal:  Epidemiol Infect       Date:  2017-02-22       Impact factor: 4.434

6.  Time-series analysis of tuberculosis from 2005 to 2017 in China.

Authors:  H Wang; C W Tian; W M Wang; X M Luo
Journal:  Epidemiol Infect       Date:  2018-04-30       Impact factor: 4.434

7.  Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability.

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8.  Time Series Analysis and Forecasting of the Hand-Foot-Mouth Disease Morbidity in China Using An Advanced Exponential Smoothing State Space TBATS Model.

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Journal:  Infect Drug Resist       Date:  2021-07-21       Impact factor: 4.003

9.  Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China.

Authors:  Rui Zhang; Zhen Guo; Yujie Meng; Songwang Wang; Shaoqiong Li; Ran Niu; Yu Wang; Qing Guo; Yonghong Li
Journal:  Int J Environ Res Public Health       Date:  2021-06-07       Impact factor: 3.390

10.  Spatiotemporal analysis and forecasting model of hemorrhagic fever with renal syndrome in mainland China.

Authors:  Ling Sun; Lu-Xi Zou
Journal:  Epidemiol Infect       Date:  2018-08-06       Impact factor: 4.434

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