|国家科技期刊平台
首页|期刊导航|现代医药卫生|基于ARIMA模型预测镇江市肺结核流行趋势及分析

基于ARIMA模型预测镇江市肺结核流行趋势及分析OA

Prediction and analysis of pulmonary tuberculosis epidemic trend in Zhenjiang City based on ARIMA

中文摘要英文摘要

目的 通过构建季节性差分整合移动平均自回归模型(ARIMA模型)预测江苏省镇江市肺结核流行趋势并验证模型的有效性,探讨新型冠状病毒感染疫情对肺结核流行情况的影响.方法 收集江苏省镇江市2014-2022年肺结核月发病数资料,构建季节性ARIMA模型,以2022年1-12月肺结核发病数验证预测模型效果,并分析预测误差产生的原因.结果 2014-2022年镇江市共报告肺结核病例11 316例,除2017、2019年发病率有所回升外,总体发病率呈下降趋势,发病主要集中在3-8月.ARIMA(1,1,1)(1,1,0)12的BIC值(5.913)最小,残差白噪声也通过检验.但短期自相关部分的AR系数不显著,因此建立ARIMA(0,1,1)(1,1,0)12.2022年镇江市肺结核月发病数实际值与预测值存在一定的偏差(平均相对预测误差为19.20%),但均在拟合值的95%可信区间内,实际月发病数(平均78例/月)与预测值(平均78例/月)变化趋势基本一致,模型拟合度较好,可用于预测镇江市肺结核流行情况.结论 利用该模型对短期内镇江市肺结核发病数进行预测,认为镇江市肺结核流行总体上仍将长期保持下行趋势.

Objective To predict the trend of pulmonary tuberculosis prevalence in Zhenjiang City of Jiangsu Province by constructing a seasonal autoregressive integrated moving average(ARIMA)model and verify the effectiveness of the model,and to explore the impact of the COVID-19 pandemic on the prevalence state of pulmonary tuberculosis.Methods The pulmonary tuberculosis monthly incidence data during 2014-2022 in Zhenjiang City of Jiangsu Province were collected to construct a seasonal ARIMA model.The model's predictive performance was validated by using the onset number of pulmonary tuberculosis from January to December 2022,and the causes of prediction errors were analyzed.Results A total of 1 316 cases of pulmona-ry tuberculosis were reported in Zhenjiang City during 2014-2022.The overall incidence rate showed a down-ward trend,except for the slight increase in 2017,2019.The onset was mainly concentrated from March to Au-gust.The ARIMA model with parameters(1,1,1)(1,1,0)12 had the lowest BIC value(5.913),and the white noise residuals also passed the test.However,the AR coefficient in the short-term autocorrelation was not sig-nificant,so the ARIMA model with parameters(0,1,1)(1,1,0)12 was established.There was a certain devia-tion between the actual value and predictive value in monthly incidence number of pulmonary tuberculosis in Zhenjiang City during 2022(average relative prediction error of 19.20%).However,all were within the 95%confidence interval of the fitted values.The change trend of the actual monthly incidence number(average 78 cases/month)was basically consistent with the predicted value(average 78 cases/month).The model fitting degree was well and could be used to predict the epidemiological situation of pulmonary tuberculosis in Zhen-jiang City.Conclusion This model is used to predict the incidence number of pulmonary tuberculosis in Zhen-jiang City in the short term,and it is considered that the overall trend of pulmonary tuberculosis epidemic in Zhenjiang City will remain the downward trend in the long run.

伍鸿远;夏媛媛

南京医科大学医政学院,江苏 南京 211166

临床医学

ARIMA模型肺结核传染病预测新型冠状病毒感染镇江

Autoregressive Integrated Moving Average modelTuberculosisPrediction of infec-tious diseasesCOVID-19Zhenjiang

《现代医药卫生》 2024 (001)

20-25,30 / 7

国家社会科学基金重大项目(20&ZD224);江苏高校哲学社会科学重点研究基地项目(2020RWPT0101);国家级大学生创新创业训练计划(202210312047Z).

10.3969/j.issn.1009-5519.2024.01.004

评论