Abstract

Objective: To analyze the epidemiologic characteristics and distribution of influenza in China from 2010 to 2019, and predict the incidence trends of all types of influenza. Methods: Seasonal ARIMA model was used for original series pre-process, model identification, parameters estimation and statistical modeling to predict the incidence trend of influenza. Results: The influenza time series model constructed was ARIMA (1,2,1) (0,1,1)12, and the data information was fully extracted (Q=14.257, P>0.05), the relative error was about 10%. Influenza A prediction model was ARIMA (2,1,1) (0,2,2)12, the data information was fully extracted (Q=13.236, P>0.05). The predicted incidence of influenza A was high from December 2018 to March 2019, and the incidence decreased rapidly from April, similar to the actual situation. Relative error was controlled within 10%; The influenza B prediction model was ARIMA (1,2,1) (1 …

Metadata

publication

year

2022

publication date

2022/11/29

authors

Hao-yun Dai, Nan Zhou, Xiang Ren, Piao-yi Luo, Shang-hui Yi, Mei-fang Quan, Wen-ting Zha, Yuan Lyu

link

https://www.cabidigitallibrary.org/doi/full/10.5555/20220530070

volume

37

issue

10

pages

1338-1345