ArticlePloS one2018
Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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Who cites it
61 citing papers in PubMed, 157 citations in OpenAlex.
- Forecasting monthly hepatitis B cases in China: a nationwide comparative study based on surveillance data.BMC public health · 2026Article
- Time-Series Analysis and Age-Stratified Forecasting of Diarrheal Disease in Rwanda Using SARIMA Models.Tropical medicine and infectious disease · 2026Article
- Early warning of hepatitis B epidemics in Henan Province, China, from 2014 to 2023 based on Baidu Index and Bayesian Structural Time Series model.Archives of public health = Archives belges de sante publique · 2026Article
- Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model.BMC public health · 2025Article
- Temporal Trends in the Burden of Disease for Male Infertility from 1990 to 2021 in the BRICS.Risk management and healthcare policy · 2025Article
- Trend analysis of pediatric urolithiasis prevalence from 1990 to 2021 in the BRICS.Frontiers in pediatrics · 2025Article
- Wild mushroom poisoning in Mengzi city, Yunnan province, China, 2018-2023: an analysis through epidemiological characteristics and time series analysis with SARIMA and holt-winters models.Frontiers in toxicology · 2025Article
- Evaluating the effectiveness of self-attention mechanism in tuberculosis time series forecasting.BMC infectious diseases · 2024Article
- Spatiotemporal risk of human brucellosis under intensification of livestock keeping based on machine learning techniques in Shaanxi, China.Epidemiology and infection · 2024Article
- Spatial and temporal analysis and forecasting of TB reported incidence in western China.BMC public health · 2024Article
- Predicting the epidemiological trend of acute hemorrhagic conjunctivitis in China using Bayesian structural time-series model.Scientific reports · 2024Article
- Temporal trend analysis of acute hepatitis B virus infection in China, 1990-2019.Epidemiology and infection · 2024Article
- Evaluating the impact of COVID-19 outbreak on hepatitis B and forecasting the epidemiological trend in mainland China: a causal analysis.BMC public health · 2024Article
- Comparison of ARIMA and Bayesian Structural Time Series Models for Predicting the Trend of Syphilis Epidemic in Jiangsu Province.Infection and drug resistance · 2024Article
- Temporal disruption in tuberculosis incidence patterns during COVID-19: a time series analysis in China.PeerJ · 2024Article
- 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
- Retrospective evaluation of short-term forecast performance of ensemble sub-epidemic frameworks and other time-series models: The 2022-2023 mpox outbreak across multiple geographical scales, July 14medRxiv : the preprint server for health sciences · 2023Article
- Vaccine rate forecast for COVID-19 in Africa using hybrid forecasting models.African health sciences · 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
1 more citing papers are in PubMed but not listed here.
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3 authors at 1 institution in 1 country.
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Abstract
backgroundHepatitis B virus (HBV) infection is a major public health threat in China for China has a hepatitis B prevalence of more than one million people in 2017 year. Disease incidence prediction may help hepatitis B prevention and control. This study intends to build and compare 2 forecasting models for hepatitis B incidence in China.
methodsAutoregressive integrated moving average (ARIMA) model and grey model GM(1,1) were adopted to fit the monthly incidence of hepatitis B in China from March 2010 to October 2017. The fitting and forecasting performances of the 2 models were evaluated. The better one was adopted to predict the incidence from November 2017 to March 2018. Database was built by Excel 2016 and statistical analysis was completed using R 3.4.3 software.
resultsDescriptive analysis showed that the incidence of hepatitis B in China has seasonal variation and has shown a downward trend from 2010 to 2017. We selected the ARIMA (3,1,1) (0,1,2)12 model among all the ARIMA models for it has the lowest AIC value. Model expression of GM (1,1) was X(1) (k + 1) = 3386876.7478e0.0249k - 3289206.7428. The root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA(3,1,1)(0,1,2)12 model were lower than GM(1,1) model on fitting part and forecasting part. According to the forecast results, the incidence may have a slight fluctuation during the following months.
conclusionsThe ARIMA model showed better hepatitis B fitting and forecasting performance than GM(1,1) model. It is a potential decision supportive tool for controlling hepatitis B in China before a predictive hepatitis B outbreak.
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