ArticleFrontiers in public health2024
Exploring the influence of environmental indicators and forecasting influenza incidence using ARIMAX models.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Forecasting seasonal allergic rhinitis through integrated analysis of social media and online drug sales data.The World Allergy Organization journal · 2026Article
- Research on influenza surveillance and a prediction model based on multi-source data.BMC medical informatics and decision making · 2026Article
- An ARIMAX model integrating Baidu index for improved hand, foot, and mouth disease incidence prediction.Scientific reports · 2026Article
- Generalized additive model integrating multi-source data for short-term influenza forecasting in Shenzhen, China (2023-2025).Frontiers in public health · 2026Article
- Incorporating meteorological factors into a SARIMA model for predicting pediatric influenza epidemics.Frontiers in public health · 2026Article
- Nationwide population-level influenza cycle threshold values and trends in influenza incidence: a longitudinal study.Scientific reports · 2025Article
- Dynamic ensemble deep learning with multi-source data for robust influenza forecasting in Yangzhou.BMC public health · 2025Article
- The bill of aging: fiscal projections of demographic changes on South Korea's national health insurance, 2023-2042.Health economics review · 2025Article
- Long short-term memory-based forecasting of influenza epidemics using surveillance and meteorological data in Tokyo, Japan.Frontiers in public health · 2025Article
- Improving influenza prediction in Quanzhou, China: an ARIMAX model integrated with meteorological drivers.Frontiers in public health · 2025Article
- Temporal dynamics and forecasting of respiratory viral infections during and after the SARS-CoV-2 pandemic (2020-2027): a multiplex PCR and ARIMA-based study.Frontiers in microbiology · 2025Article
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7 authors.
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Abstract
Background: Influenza is a respiratory infection that poses a significant health burden worldwide. Environmental indicators, such as air pollutants and meteorological factors, play a role in the onset and propagation of influenza. Accurate predictions of influenza incidence and understanding the factors influencing it are crucial for public health interventions. Our study aims to investigate the impact of various environmental indicators on influenza incidence and apply the ARIMAX model to integrate these exogenous variables to enhance the accuracy of influenza incidence predictions. Method: Descriptive statistics and time series analysis were employed to illustrate changes in influenza incidence, air pollutants, and meteorological indicators. Cross correlation function (CCF) was used to evaluate the correlation between environmental indicators and the influenza incidence. We used ARIMA and ARIMAX models to perform predictive analysis of influenza incidence. Results: From January 2014 to September 2023, a total of 21,573 cases of influenza were reported in Fuzhou, with a noticeable year-by-year increase in incidence. The peak of influenza typically occurred around January each year. The results of CCF analysis showed that all 10 environmental indicators had a significant impact on the incidence of influenza. The ARIMAX(0, 0, 1) (1, 0, 0) Conclusion: This study provides insights into the impact of environmental indicators on influenza incidence in Fuzhou. The ARIMAX(0, 0, 1) (1, 0, 0)
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