我国2012-2021年4种肝炎流行趋势的时间序列分析和预测OACSTPCD

Objective:To analyze the seasonal patterns and long-term trends of the 10 year epidemic characteristics of four types of viral hepatitis in China from 2012 to 2021,and explore a time series model suitable for forecasting predicting hepatitis incidence,providing reference and suggestions for scientific hepatitis prevention and control.Methods:Seasonal decomposition of the time series was conducted on the monthly incidence of hepatitis A,B,C,and E in China from January 2012 to December 2021.A seasonal autoregressive integrated moving average model(ARIMA)and a seasonal index smoothing model(ES)were established to predict the incidence of four types of hepatitis from January to August 2022,and the predictive effects were compared.Results:March of each year is the peak period for the incidence of all types of hepatitis.Over the 10 year period,the hepatitis A showed an overall decreasing trend,hepatitis B had fluctuating trends with recent years showing an increasing trend,hepatitis C showed an overall increasing trend,and hepatitis E remained stable overall.The monthly average incidence of hepatitis B,C,and E were 57.06 times,11.5 times,and 1.35 times higher than that of hepatitis A,respectively.The prediction performance of the seasonal ES model was better than that of the seasonal ARIMA model.Conclusion:There are a large number of patients with hepatitis B and C in China,and key prevention and control efforts need to be strengthened.The seasonal decomposition of time series can be used to analyze the seasonal patterns and long-term trends of hepatitis prevalance.The seasonal ES model includes three parameters:level,trend,and seasonality,which can reflect the epidemic pattern of hepatitis.In the prediction of hepatitis incidence,it has the advantages of being simple,easy to calculate,and high prediction accuracy.