Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model

Zou Xiaojiang; Zhao Han; Wang Qiyin; Ye Mengliang

doi:10.13406/j.cnki.cyxb.003384

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Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model

Disease data analysis and modeling | 更新时间：2025-10-22

- Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model
- Journal of Chongqing Medical University Vol. 48, Issue 12, Pages: 1425-1429(2023)
- 作者机构：
  
  1.重庆医科大学公共卫生学院，重庆 400016
  2.重庆市疾病预防控制中心，重庆 400000
- 作者简介：
- 基金信息：
- DOI：10.13406/j.cnki.cyxb.003384
  CLC： R511.7
- Received：05 September 2023，
  
  Revised：2023-11-10，
  
  Accepted：10 December 2023，
  
  Published：28 December 2023
- 稿件说明：
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邹小江,赵寒,王祈茵,等.基于ARIMA模型的重庆市流行性感冒预测研究[J].重庆医科大学学报,2023,48(12):1425-1429.

Zou Xiaojiang,Zhao Han,Wang Qiyin,et al.Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model[J].Journal of Chongqing Medical University,2023,48(12):1425-1429.
邹小江,赵寒,王祈茵,等.基于ARIMA模型的重庆市流行性感冒预测研究[J].重庆医科大学学报,2023,48(12):1425-1429. DOI： 10.13406/j.cnki.cyxb.003384.

Zou Xiaojiang,Zhao Han,Wang Qiyin,et al.Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model[J].Journal of Chongqing Medical University,2023,48(12):1425-1429. DOI： 10.13406/j.cnki.cyxb.003384.

摘要

目的

分析流感的流行趋势，构建流行性感冒发病的自回归滑动平均混合模型（autoregressive integrated moving average，ARIMA）并对验证集进行预测，为重庆市流感的防治提供科学依据。

方法

本研究采用R软件对重庆市2010年1月至2021年6月的流感数据进行ARIMA模型拟合，用2021年7月至2021年12月的数据评价模型拟合效果。

结果

该流感疾病的流行呈现出明显的季节周期性，周期为1年，发病高峰期为冬季和春季，整体患病率呈上升后有下降趋势，拟合最佳模型为

ARIMA

（0，1，2）×（0，1，2）

，且该模型在预测2021年7月至12月罹患率的均方根误差为10.70，平均绝对百分比误差为70.04%，预测效果较好。

结论

ARIMA模型在预测重庆市流感发病和流行趋势上有一定的效果，并能对未来的罹患率进行估计，可以为今后的流感疾病防控工作提供参考。

Abstract

Objective

To investigate the trend of influenza prevalence by constructing an Autoregressive Integrated Moving Average （ARIMA） model for influenza and making predictions on the validation set，and to provide a scientific basis for the prevention and control of influenza in Chongqing，China.

Methods

In this study，R software was used for the ARIMA model fitting of influenza data in Chongqing from January 2010 to June 2021，and the data from July to December 2021 were used to evaluate the fitting performance of the model.

Results

The prevalence of this influenza disease presented with a noticeable seasonal pattern，with a yearly cycle and a peak in winter and spring. The overall prevalence rate tended to increase first and then decrease，and the best-fitting model was

ARIMA

（0，1，2）×（0，1，2）

，which had a root mean square error of 10.70 and a mean absolute percentage error of 70.04% in predicting the attack rate in July to December 2021，suggesting that the model had good predictive efficacy.

Conclusion

The ARIMA model has a certain effect in predicting the onset and prevalence trend of influenza in Chongqing and can estimate the attack rate of influenza in the future，which can provide a reference for the prevention and control of influenza in the future.

关键词

Keywords

references

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