• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

中国大陆地区乙型肝炎的 SARIMA 模型预测研究。

The research of SARIMA model for prediction of hepatitis B in mainland China.

机构信息

Department of Medical Administration, Sichuan Provincial Orthopedics Hospital, Chengdu, Sichuan, China.

Department of Medical Administration, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan, China.

出版信息

Medicine (Baltimore). 2022 Jun 10;101(23):e29317. doi: 10.1097/MD.0000000000029317.

DOI:10.1097/MD.0000000000029317
PMID:35687775
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9276452/
Abstract

Hepatitis B virus infection is a major global public health concern. This study explored the epidemic characteristics and tendency of hepatitis B in 31 provinces of mainland China, constructed a SARIMA model for prediction, and provided corresponding preventive measures.Monthly hepatitis B case data from mainland China from 2013 to 2020 were obtained from the website of the National Health Commission of the People's Republic of China. Monthly data from 2013 to 2020 were used to build the SARIMA model and data from 2021 were used to test the model.Between 2013 and 2020, 9,177,313 hepatitis B cases were reported in mainland China. SARIMA(1,0,0)(0,1,1)12 was the optimal model and its residual was white noise. It was used to predict the number of hepatitis B cases from January to December 2021, and the predicted values for 2021 were within the 95% confidence interval.This study suggests that the SARIMA model simulated well based on epidemiological trends of hepatitis B in mainland China. The SARIMA model is a feasible tool for monitoring hepatitis B virus infections in mainland China.

摘要

乙型肝炎病毒感染是一个全球性的主要公共卫生关注点。本研究旨在探讨中国大陆 31 个省份乙型肝炎的流行特征和趋势，构建 SARIMA 模型进行预测，并提供相应的预防措施。

从中华人民共和国国家卫生健康委员会的网站上获取了中国大陆 2013 年至 2020 年每月的乙型肝炎病例数据。使用 2013 年至 2020 年的数据构建 SARIMA 模型，并使用 2021 年的数据对模型进行测试。

2013 年至 2020 年期间，中国大陆共报告乙型肝炎病例 9177313 例。SARIMA（1,0,0）（0,1,1）12 是最佳模型，其残差为白噪声。利用该模型对 2021 年 1 月至 12 月的乙型肝炎病例数进行预测，2021 年的预测值在 95%置信区间内。

本研究表明，SARIMA 模型基于中国大陆乙型肝炎的流行趋势进行了很好的模拟。SARIMA 模型是监测中国大陆乙型肝炎病毒感染的一种可行工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/c1a541ad3876/medi-101-e29317-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/82977edef35a/medi-101-e29317-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/d729d466eeff/medi-101-e29317-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/8baebfb085e3/medi-101-e29317-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/f6046ee174e4/medi-101-e29317-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/cfaa19584ba9/medi-101-e29317-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/38fb98e88f46/medi-101-e29317-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/a0971bb5d4d1/medi-101-e29317-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/c1a541ad3876/medi-101-e29317-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/82977edef35a/medi-101-e29317-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/d729d466eeff/medi-101-e29317-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/8baebfb085e3/medi-101-e29317-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/f6046ee174e4/medi-101-e29317-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/cfaa19584ba9/medi-101-e29317-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/38fb98e88f46/medi-101-e29317-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/a0971bb5d4d1/medi-101-e29317-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bae9/9276452/c1a541ad3876/medi-101-e29317-g008.jpg

相似文献

1
The research of SARIMA model for prediction of hepatitis B in mainland China.中国大陆地区乙型肝炎的 SARIMA 模型预测研究。
Medicine (Baltimore). 2022 Jun 10;101(23):e29317. doi: 10.1097/MD.0000000000029317.
2
Prediction of reported monthly incidence of hepatitis B in Hainan Province of China based on SARIMA-BPNN model.基于 SARIMA-BPNN 模型预测中国海南省报告的乙型肝炎月发病率。
Medicine (Baltimore). 2023 Oct 13;102(41):e35054. doi: 10.1097/MD.0000000000035054.
3
Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China.中国大陆手足口病发病率的混合模型预测研究。
BMC Public Health. 2023 Mar 31;23(1):619. doi: 10.1186/s12889-023-15543-9.
4
Predicting Seasonal Influenza Based on SARIMA Model, in Mainland China from 2005 to 2018.基于 SARIMA 模型预测 2005 年至 2018 年中国大陆的季节性流感。
Int J Environ Res Public Health. 2019 Nov 27;16(23):4760. doi: 10.3390/ijerph16234760.
5
The research on TBATS and ELM models for prediction of human brucellosis cases in mainland China: a time series study.中国大陆人类布鲁氏菌病病例预测的 TBATS 和 ELM 模型研究：一项时间序列研究。
BMC Infect Dis. 2022 Dec 12;22(1):934. doi: 10.1186/s12879-022-07919-w.
6
Temporal trends analysis of tuberculosis morbidity in mainland China from 1997 to 2025 using a new SARIMA-NARNNX hybrid model.利用 SARIMA-NARNNX 混合模型分析 1997 年至 2025 年中国大陆结核病发病率的时间趋势。
BMJ Open. 2019 Jul 31;9(7):e024409. doi: 10.1136/bmjopen-2018-024409.
7
A new hybrid model SARIMA-ETS-SVR for seasonal influenza incidence prediction in mainland China.一种用于中国大陆季节性流感发病率预测的新型SARIMA-ETS-SVR混合模型。
J Infect Dev Ctries. 2023 Nov 30;17(11):1581-1590. doi: 10.3855/jidc.18037.
8
Time series analysis-based seasonal autoregressive fractionally integrated moving average to estimate hepatitis B and C epidemics in China.基于时间序列分析的季节性自回归分数阶积分移动平均模型估计中国乙型和丙型肝炎流行情况。
World J Gastroenterol. 2023 Nov 14;29(42):5716-5727. doi: 10.3748/wjg.v29.i42.5716.
9
Trend analysis and prediction of gonorrhea in mainland China based on a hybrid time series model.基于混合时间序列模型的中国大陆淋病趋势分析与预测。
BMC Infect Dis. 2024 Jan 22;24(1):113. doi: 10.1186/s12879-023-08969-4.
10
Forecasting the incidence of tuberculosis in China using the seasonal auto-regressive integrated moving average (SARIMA) model.应用季节性自回归求和移动平均（SARIMA）模型预测中国结核病发病率。
J Infect Public Health. 2018 Sep-Oct;11(5):707-712. doi: 10.1016/j.jiph.2018.04.009. Epub 2018 May 3.

引用本文的文献

1
Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model.基于贝叶斯结构化时间序列模型评估河南省新冠肺炎对乙型肝炎的影响及其流行趋势
BMC Public Health. 2025 Apr 8;25(1):1312. doi: 10.1186/s12889-025-22305-2.
2
Prediction analysis of human brucellosis cases in Ili Kazakh Autonomous Prefecture Xinjiang China based on time series.基于时间序列的中国新疆伊犁哈萨克自治州人间布鲁氏菌病病例预测分析
Sci Rep. 2025 Jan 7;15(1):1232. doi: 10.1038/s41598-024-80513-z.
3
Spatial and temporal analysis and forecasting of TB reported incidence in western China.
中国西部地区结核病报告发病率的时空分析与预测。
BMC Public Health. 2024 Sep 13;24(1):2504. doi: 10.1186/s12889-024-19994-6.
4
Trends and multi-model prediction of hepatitis B incidence in Xiamen.厦门乙肝发病率的趋势及多模型预测
Infect Dis Model. 2024 Aug 6;9(4):1276-1288. doi: 10.1016/j.idm.2024.08.001. eCollection 2024 Dec.
5
Enhancing infectious disease prediction model selection with multi-objective optimization: an empirical study.利用多目标优化改进传染病预测模型选择：一项实证研究
PeerJ Comput Sci. 2024 Jul 29;10:e2217. doi: 10.7717/peerj-cs.2217. eCollection 2024.
6
Trend analysis and prediction of gonorrhea in mainland China based on a hybrid time series model.基于混合时间序列模型的中国大陆淋病趋势分析与预测。
BMC Infect Dis. 2024 Jan 22;24(1):113. doi: 10.1186/s12879-023-08969-4.
7
Trends and Patterns of Systemic Glucocorticoid Prescription in Primary Care Institutions in Southwest China, from 2018 to 2021.2018年至2021年中国西南部基层医疗机构全身糖皮质激素处方的趋势与模式
Risk Manag Healthc Policy. 2023 Dec 21;16:2849-2868. doi: 10.2147/RMHP.S436747. eCollection 2023.
8
Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China.中国大陆手足口病发病率的混合模型预测研究。
BMC Public Health. 2023 Mar 31;23(1):619. doi: 10.1186/s12889-023-15543-9.