ArticleChina CDC weekly2023
An Autoregressive Integrated Moving Average Model for Predicting Varicella Outbreaks - China, 2019.
Article in China CDC weekly, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Global burden of varicella in children aged 5-9 y, relationship with vaccination policy indicators, and projected trends to 2030.Human vaccines & immunotherapeutics · 2026Article
- Temporal trends in prevalence and years of life lived with disability for hearing loss in China from 1990 to 2021: an analysis of the global burden of disease study 2021.Frontiers in public health · 2025Article
- The burden of Parkinson's disease, 1990-2021: a systematic analysis of the Global Burden of Disease study 2021.Frontiers in aging neuroscience · 2025Article
- A trend analysis of the burden of lower extremity peripheral arterial disease in China, 1990 to 2021: based on the Global Burden of Disease Study 2021.Frontiers in public health · 2025Article
- Trajectories tracking of maternal and neonatal health in eastern China from 2010 to 2021: A multicentre cross-sectional study.Journal of global health · 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
- Exploring the influence of environmental indicators and forecasting influenza incidence using ARIMAX models.Frontiers in public health · 2024Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Varicella, a prevalent respiratory infection among children, has become an escalating public health issue in China. The potential to considerably mitigate and control these outbreaks lies in surveillance-based early warning systems. This research employed an autoregressive integrated moving average (ARIMA) model with the objective of predicting future varicella outbreaks in the country. Methods: An ARIMA model was developed and fine-tuned using historical data on the monthly instances of varicella outbreaks reported in China from 2005 to 2018. To determine statistically significant models, parameter and Ljung-Box tests were employed. The coefficients of determination (R Results: Four models passed parameter (all Conclusion: The ARIMA model can be employed to predict impending trends in varicella outbreaks. This serves to offer a scientific benchmark for strategies concerning varicella prevention and control.
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