ArticleChina CDC weekly2022
Comparing COVID-19 Case Prediction Between ARIMA Model and Compartment Model - China, December 2019-April 2020.
Article in China CDC weekly, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Respiratory pathogen dynamics in community fever cases: Jiangsu Province, China (2023-2024).Virology journal · 2024Article
- Theoretical Epidemiology Needs Urgent Attention in China.China CDC weekly · 2024Article
- An Autoregressive Integrated Moving Average Model for Predicting Varicella Outbreaks - China, 2019.China CDC weekly · 2023Article
- COVID-19 Patterns in Araraquara, Brazil: A Multimodal Analysis.International journal of environmental research and public health · 2023Article
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Authors and funding
4 authors.
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Abstract
Introduction: To compare the performance between the compartment model and the autoregressive integrated moving average (ARIMA) model that were applied to the prediction of new infections during the coronavirus disease 2019 (COVID-19) epidemic. Methods: The compartment model and the ARIMA model were established based on the daily cases of new infection reported in China from December 2, 2019 to April 8, 2020. The goodness of fit of the two models was compared using the coefficient of determination (R Results: The compartment model predicts that the number of new cases without a cordon sanitaire, i.e., a restriction of mobility to prevent spread of disease, will increase exponentially over 10 days starting from January 23, 2020, while the ARIMA model shows a linear increase. The calculated R Discussion: The two models fit well at different stages of the epidemic. The predictions of compartment model were more in line with highly contagious transmission characteristics of COVID-19. The accuracy of recent historical data had a large impact on the predictions of the ARIMA model as compared to those of the compartment model.
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