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SARIMA模型在重庆市水痘发病率预测中的应用

王菊 李柏松 彭杨 熊宇 杨举乐 李知晋 漆莉 龙江

保健医学研究与实践2025,Vol.22Issue(4):35-41,7.
保健医学研究与实践2025,Vol.22Issue(4):35-41,7.DOI:10.11986/j.issn.1673-873X.2025.04.06

SARIMA模型在重庆市水痘发病率预测中的应用

Application of a SARIMA model in predicting varicella incidence in Chongqing

王菊 1李柏松 1彭杨 2熊宇 1杨举乐 1李知晋 3漆莉 1龙江1

作者信息

  • 1. 重庆市疾病预防控制中心(重庆市预防医学科学院)传防所,重庆 400707
  • 2. 重庆市璧山区疾病预防控制中心传防所,重庆 402700
  • 3. 西南医科大学公共卫生学院,四川 泸州 646099
  • 折叠

摘要

Abstract

Objective To explore the application of the Seasonal Autoregressive Integrated Moving Average(SARIMA)model in predicting varicella incidence trends in Chongqing based on surveillance data.Methods Varicella case data and population data from January 2015 to December 2024 were retrieved from the Infectious Disease Reporting Information Management Sys-tem.R software was used to construct the optimal SARIMA model for monthly varicella incidence in Chongqing.The model was used to predict the reported incidence of varicella from January to December 2024,with predictions compared against actual values.Model fit was evaluated using mean absolute error and other metrics.Varicella incidence for January to December 2025 was forecasted.Results From 2015 to 2019,reported varicella incidence in Chongqing showed an upward trend,while fluctua-ting changes with an overall downward trend occurred from 2020 to 2024.The SARIMA(1,0,1)(0,1,2)12 model was optimal,with goodness-of-fit R2=0.896 and Bayesian Information Criterion=475.356.Residuals constituted a white noise series,and all model parameters passed statistical tests.For predictions from January to December 2024,the mean absolute error between actual and fitted values was 1.182,the root mean square error was 1.660,and the mean percentage error was-1.263%,mean absolute percetage error was 23.841%indicating reasonable model performance.Conclusion The constructed SARIMA(1,0,1)(0,1,2)12 model demonstrates satisfactory fit and can be used for short-term prediction of varicella incidence trends in Chongqing,providing certain guiding implications for developing varicella prevention and control measures.

关键词

水痘/季节性差分自回归移动平均模型/时间序列分析/预测

Key words

Varicella/SARIMA model/Time series analysis/Prediction

分类

医药卫生

引用本文复制引用

王菊,李柏松,彭杨,熊宇,杨举乐,李知晋,漆莉,龙江..SARIMA模型在重庆市水痘发病率预测中的应用[J].保健医学研究与实践,2025,22(4):35-41,7.

基金项目

重庆市卫生健康委医学科研项目(2024WSJK070) (2024WSJK070)

国家自然科学基金(12371503). (12371503)

保健医学研究与实践

1673-873X

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