ArticleComputational and mathematical methods in medicine2022
Prediction of Incidence Trend of Influenza-Like Illness in Wuhan Based on ARIMA Model.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Data-Driven Machine Learning-Based Forecasting of Dengue in Bangladesh: Supporting Digital Health Approaches for Early Warning.Health science reports · 2026Article
- Analysis and forecast of hand, foot, and mouth disease epidemic trends in Guangzhou, China, 2013-2023.PloS one · 2025Article
- Predicting the epidemiological trend of acute hemorrhagic conjunctivitis in China using Bayesian structural time-series model.Scientific reports · 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
- Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China.BMC public health · 2023Article
- Estimation of influenza incidence and analysis of epidemic characteristics from 2009 to 2022 in Zhejiang Province, China.Frontiers in public health · 2023Article
- Retracted: Prediction of Incidence Trend of Influenza-Like Illness in Wuhan Based on ARIMA Model.Computational and mathematical methods in medicine · 2023Article
Corrections and comments
- Retraction · 2023-09-27Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/D030CE82FDE47F6E1B4FD2BECB3AA5
- Retracted
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The autoregressive integrated moving average (ARIMA) model has been widely used to predict the trend of infectious diseases. This paper is aimed at analyzing the application of the ARIMA model in the prediction of the incidence trend of influenza-like illness (ILI) in Wuhan and providing a scientific basis for the prediction and prevention of influenza. Methods: The weekly ILI data of two influenza surveillance sentinel hospitals in Wuhan City published on the website of the National Influenza Center of China were collected, and the ARIMA model was used to model the data from 2014 to 2020, to predict and verify the ILI data in 2021. Results: The optimal model for the incidence trend of ILI in Wuhan was ARIMA (1, 1, 1), the residuals were in line with the white noise sequence (0.018 < Ljung-Box Conclusion: ARIMA (1, 1, 1) can effectively simulate the short-term incidence trend of ILI in Wuhan.
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