摘要
目的利用时间序列干预分析模型研究新型冠状病毒感染疫情对乙类呼吸道传染病时间序列数据的具体影响。方法以新型冠状病毒感染疫情和季节因素为干预变量,对2017-2021年北京市乙类呼吸道传染病的时间序列进行干预分析,利用R语言TSA包中的arimax函数定量分析新型冠状病毒感染疫情对乙类呼吸道传染病的影响及预测。结果根据X11季节调节模型构建季节指数得出,2017-2021年北京市乙类呼吸道传染病的波峰在5-6月和11-12月。干预分析模型考虑新型冠状病毒感染疫情和季节因素建立回归模型,选取最优拟合模型,新型冠状病毒感染疫情后乙类呼吸道传染病报告发病数较之前下降了35.5%。在新型冠状病毒感染疫情和季节因素不变的情况下,模型预测未来一年报告发病数。结论新型冠状病毒感染疫情影响了乙类呼吸道传染病时间序列,致使北京市其他乙类呼吸道传染病病例报告数降低。干预分析可以较好地处理事件发生前后影响的时间序列问题。
Objective A time series intervention analysis model to study the specific effect of COVID-19 on the time series data of class B respiratory infectious diseases.Methods Using COVID-19 and seasonal factors as intervention variables,the time series of class B respiratory infectious diseases in Beijing in 2017-2021 years were analyzed.Quantitative analysis of the influence and prediction of COVID-19 on class B respiratory infectious diseases was conducted by using arimax function in R language TSA package.Results According to the seasonal index constructed by X11 seasonal regulation model,the peaks of class B respiratory infectious diseases in Beijing from 2017 to 2021 were from May to June and from November to December.The intervention analysis model had considered COVID-19 and seasonal factors to establish regression models,and the best fitting model was selected.The number of reported cases of respiratory infectious diseases decreased 35.5%after the epidemic of COVID-19 than before.In the case of COVID-19 and seasonal factors,the number of reported cases in the coming year was predicted by the model.Conclusions The epidemic of COVID-19 affected the time series of class B respiratory infectious diseases and reduced the number of case reports.And the intervention analysis could better deal with the time series of the impact before and after the event.
作者
周滢
李刚
王超
史芸萍
虎霄
刘洋
李伟
高燕琳
ZHOU Ying;LI Gang;WANG Chao;SHI Yun-ping;HU Xiao;LIU Yang;LI Wei;GAO Yan-lin(Beijing Center for Disease Prevention and Control,Beijing 100013,China)
出处
《首都公共卫生》
2023年第1期19-24,共6页
Capital Journal of Public Health
基金
首都卫生发展科研专项(编号:2021-1G-3013)。
关键词
干预分析
ARIMAX模型
新型冠状病毒感染
乙类呼吸道传染病
预测
Intervention analysis
Arimax model
Coronavirus disease 2019(COVID-19)
Class B respiratory infectious diseases
Forecast
作者简介
通信作者:高燕琳,E-mail:gaoyl@bjcdc.org。
