摘要
目的描述2010-2018年四川省流行性感冒(流感)流行病学特征,构建时间序列(Autoregressive Integrated Moving Average,ARIMA)模型,分析其时空变化趋势,为流感的综合防控提供参考依据。方法对2010-01/2018-12四川省流感发病情况进行分析,构建月度发病数ARIMA时间序列模型和年度空间分布专题地图,分析四川地区流感时空流行特征及趋势。结果 2010-2018年四川省流感疫情稳中有升,近年来发病水平上升显著;全省疫情出现由西北人口稀少区域向中东部人口密集区域演变的趋势,发病高峰以冬春季为主。ARIMA(2,1,3)(1,1,1)12预测2019年流感报告发病数高于2018年发病数。结论 ARIMA模型能够较好地对四川省流感疫情报告发病数进行拟合和短期预测,流感疫情呈现的时空分布特征及其趋势能够为流感风险评估、重点地区和重点人群筛选等综合防控提供参考依据。
Objective To describe the epidemiological characteristics of influenza in Sichuan province from 2010 to 2018, to build a time series autoregressive moving average model-Autoregressive Integrated Moving Average model(ARIMA model), to predict the incidence of influenza in Sichuan province in 2019, and to discuss the model application in the prediction of influenza incidence trends. Methods ARIMA model was constructed and the incidence trend of influenza in2019 was predicted based on the epidemiological characteristics of influenza monitoring data from January 2010 to December 2018 in Sichuan province. Results The incidence of influenza in Sichuan province showed an overall upward trend from2010 to 2018,but obviously rise in recent years.The trend of the epidemic situation in the whole province is from the sparsely populated areas in northwest to the densely populated areas in the central and Eastern regions,with the peak incidence in winter and spring. ARIMA(2,1,3)(1,1,1)12 could appropriately fit the time series of the influenza from 2010 to 2018, and predicted more cases of influenza in 2019 than that in 2018. Conclusion ARIMA model can be used for short-term prediction of the incidence of influenza. Comprehensive analysis of the spatial and temporal distribution characteristics and trends of influenza can provide reference for the comprehensive prevention and control of influenza such as risk assessment,screening of key areas and populations.
作者
祝小平
刘伦光
陈秀伟
孙唯
张瑶
袁珩
杨长虹
魏荣杰
ZHU Xiaoping;LIU Lunguang;CHEN Xiuwei;SUN Wei;ZHANG Yao;YUAN Heng;YANG Changhong;WEI Rongjie(Sichuan Center for Diseases Control and Prevention,Sichuan Province,Chengdu 610041,China)
出处
《预防医学情报杂志》
CAS
2020年第9期1097-1102,共6页
Journal of Preventive Medicine Information
基金
四川省科技计划项目(项目编号:2020YFS0001)
四川省科技计划项目(项目编号:2020YFS0007)。
