Prediction of reported monthly incidence of hepatitis B in Hainan Province of China based on SARIMA-BPNN model

Author:

Fang Kang1ORCID,Cao Li1,Fu Zhenwang2,Li Weixia1

Affiliation:

1. Department of Mathematical Statistics, International School of Public Health and One Health, Hainan Medical University, Haikou, China

2. Institute of Infectious Disease Prevention and Control, Hainan Center for Disease Control & Prevention, Haikou, Hainan, China.

Abstract

In recent years, the incidence of hepatitis B has been serious in Hainan Province of China. To construct a statistical model of the monthly incidence of hepatitis B in Hainan Province of China and predict the monthly incidence of hepatitis B in 2022. Simple central moving average method and seasonal index were used to analyze the trend and seasonal effects of monthly incidence of hepatitis B. Based on the time series of reported monthly incidence of hepatitis B in Hainan Province from 2017 to 2020, a multiplicative seasonal model (SARIMA), multiplicative seasonal model combined with error back propagation neural network model (SARIMA-BPNN), and a gray prediction model were constructed to fit the incidence, and the time series of monthly incidence of hepatitis B in 2021 was used to verify the accuracy of models. The lowest and highest monthly incidence of hepatitis B in Hainan Province were in February and August, respectively, and MAPE of SARIMA, SARIMA-BPNN, and gray prediction models were 0.089, 0.087, and 0.316, respectively. The best fitting model is the SARIMA-BPNN model. The predicted monthly incidence of hepatitis B in 2022 showed a downward trend, with the steepest decline in March, which indicates that the prevention and control of hepatitis B in Hainan Province is effective, and the study can provide scientific and reasonable suggestions for the prevention and control of hepatitis B in Hainan.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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