厦门乙型肝炎发病趋势和多模型预测

IF 8.8 3区 医学 Q1 Medicine
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引用次数: 0

摘要

背景本研究旨在分析厦门市2004年至2022年乙肝发病率的变化趋势,并筛选出预测2023年至2027年乙肝病例数的最佳模型。方法数据来源于中国疾病预防控制信息系统(CISDCP)。连接点回归模型分析了时间趋势,而年龄-时期-队列(APC)模型评估了年龄、时期和队列对乙肝发病率的影响。我们还比较了神经网络自回归(NNAR)模型、贝叶斯结构时间序列(BSTS)模型、先知指数平滑(ETS)模型、季节自回归综合移动平均(SARIMA)模型和混合模型的预测性能,选择性能最高的模型来预测未来五年的乙肝病例数。成人发病率较高,尤其是 30-39 岁年龄组。此外,时期和队列对发病率的影响也呈下降趋势。此外,在表现最佳的 NNAR(10,1,6)[12] 模型中,预测 2023 年的新增病例数为 4271 例,到 2027 年将增至 5314 例。此外,对于发病率较高的成年人,有针对性的干预措施也是必不可少的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trends and multi-model prediction of hepatitis B incidence in Xiamen

Background

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.

Methods

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.

Results

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.

Conclusions

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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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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