ArticleEpidemiology and infection2019
Time-series modelling and forecasting of hand, foot and mouth disease cases in China from 2008 to 2018.
Article in Epidemiology and infection, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- Forecasting Foodborne Disease Risk Caused byFoods (Basel, Switzerland) · 2025Article
- Harnessing hybrid perception on multi-scale features for hand-foot-mouth disease multi-region prediction based on Seq2Seq.PloS one · 2025Article
- Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model.BMC public health · 2024Article
- Epidemiology and etiology of hand, foot, and mouth disease in Zhengzhou, China, from 2009 to 2021.Infectious medicine · 2024Article
- Cross-correlation and time series analysis of rabies in different animal species in Nepal from 2005 to 2018.Heliyon · 2024Article
- Statistical machine learning models for prediction of China's maritime emergency patients in dynamic: ARIMA model, SARIMA model, and dynamic Bayesian network model.Frontiers in public health · 2024Article
- Analysis of a SARIMA-XGBoost model for hand, foot, and mouth disease in Xinjiang, China.Epidemiology and infection · 2023Article
- Comparison of SARIMA model, Holt-winters model and ETS model in predicting the incidence of foodborne disease.BMC infectious diseases · 2023Article
- Time series analysis-based seasonal autoregressive fractionally integrated moving average to estimate hepatitis B and C epidemics in China.World journal of gastroenterology · 2023Article
- Evaluation of models for multi-step forecasting of hand, foot and mouth disease using multi-input multi-output: A case study of Chengdu, China.PLoS neglected tropical diseases · 2023Article
- Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China.BMC public health · 2023Article
- Epidemiological characteristics, spatial clusters and monthly incidence prediction of hand, foot and mouth disease from 2017 to 2022 in Shanxi Province, China.Epidemiology and infection · 2023Article
- Exploring the influence of COVID-19 on the spread of hand, foot, and mouth disease with an automatic machine learning prediction model.Environmental science and pollution research international · 2023Article
- Application of logistic differential equation models for early warning of infectious diseases in Jilin Province.BMC public health · 2022Article
- Article
- Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study.Heliyon · 2022Article
- Analysis of HFMD Transmissibility Among the Whole Population and Age Groups in a Large City of China.Frontiers in public health · 2022Article
- Retrospective analysis and time series forecasting with automated machine learning of ascariasis, enterobiasis and cystic echinococcosis in Romania.PLoS neglected tropical diseases · 2021Article
- Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model.BMC infectious diseases · 2021Article
- Predictive analysis of the number of human brucellosis cases in Xinjiang, China.Scientific reports · 2021Article
Corrections and comments
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Seasonal autoregressive-integrated moving average (SARIMA) has been widely used to model and forecast incidence of infectious diseases in time-series analysis. This study aimed to model and forecast monthly cases of hand, foot and mouth disease (HFMD) in China. Monthly incidence HFMD cases in China from May 2008 to August 2018 were analysed with the SARIMA model. A seasonal variation of HFMD incidence was found from May 2008 to August 2018 in China, with a predominant peak from April to July and a trough from January to March. In addition, the annual peak occurred periodically with a large annual peak followed by a relatively small annual peak. A SARIMA model of SARIMA (1, 1, 2) (0, 1, 1)12 was identified, and the mean error rate and determination coefficient were 16.86% and 94.27%, respectively. There was an annual periodicity and seasonal variation of HFMD incidence in China, which could be predicted well by a SARIMA (1, 1, 2) (0, 1, 1)12 model.
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