Trends and multi-model prediction of hepatitis B incidence in Xiamen

入射(几何) 自回归积分移动平均 指数平滑 队列 医学 人口学 时间序列 统计 内科学 数学 几何学 社会学
作者
Ruixin Zhang,Hongfei Mi,Tingjuan He,Shifang Ren,R F Zhang,Liansheng Xu,Mingzhai Wang,Chenghao Su
出处
期刊:Infectious Disease Modelling [Elsevier]
卷期号:9 (4): 1276-1288
标识
DOI:10.1016/j.idm.2024.08.001
摘要

This study aims to analyze the trend of Hepatitis B incidence in Xiamen City from 2004 to 2022, and to select the best-performing model for predicting the number of Hepatitis B cases from 2023 to 2027. Data were obtained from the China Information System for Disease Control and Prevention (CISDCP). The Joinpoint Regression Model analyzed temporal trends, while the Age-Period-Cohort (APC) model assessed the effects of age, period, and cohort on hepatitis B incidence rates. We also compared the predictive performance of the Neural Network Autoregressive (NNAR) Model, Bayesian Structural Time Series (BSTS) Model, Prophet, Exponential Smoothing (ETS) Model, Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Hybrid Model, selecting the model with the highest performance to forecast the number of hepatitis B cases for the next five years. Hepatitis B incidence rates in Xiamen from 2004 to 2022 showed an overall declining trend, with rates higher in men than in women. Higher incidence rates were observed in adults, particularly in the 30–39 age group. Moreover, the period and cohort effects on incidence showed a declining trend. Furthermore, in the best-performing NNAR(10, 1, 6)[12] model, the number of new cases is predicted to be 4271 in 2023, increasing to 5314 by 2027. Hepatitis B remains a significant issue in Xiamen, necessitating further optimization of hepatitis B prevention and control measures. Moreover, targeted interventions are essential for adults with higher incidence rates.
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