疾病监测时间序列预测模型应用进展
Progress in the application of time series prediction models for disease monitoring
刘天 1赵婧 2吴杨 3黄淑琼3
作者信息
- 1. 荆州市疾病预防控制中心传染病防治所,湖北 荆州 434000;长江大学公共卫生研究中心,湖北 荆州 434000
- 2. 中国疾病预防控制中心,北京 102206
- 3. 湖北省疾病预防控制中心,湖北 武汉 430079
- 折叠
摘要
新型冠状病毒疫情后,如何利用疾病监测数据建立预测预警是疾病监测领域的重要研究课题.随着计算机技术的迅猛发展,近年来各类新兴时间序列模型快速增加,尚缺乏对各类疾病监测时间序列预测模型的概述.本研究对近年来国内外主要的疾病监测时间序列预测模型进行梳理,供读者了解各类疾病监测时间序列预测模型基本原理,种类,实现步骤以及模型评价指标;同时也介绍了常用的建模软件,为读者详细、全面地介绍了当前国内外疾病监测时间序列预测模型应用进展,为更好地建立预测预警模型提供重要参考.
Abstract
After the SARS-CoV-2 pandemic,how to use disease surveillance data to establish prediction and early warning is an important research topic in the field of disease surveillance.With the rapid development of computer technology,various emerging time series models have been rapidly increasing in recent years,but there is still a lack of an overview of various disease monitoring time series prediction models.This study reviews the main disease monitoring time series prediction models both domestically and internationally in recent years and provides readers with a basic understanding of the principles,classification methods,implementation steps,and model evaluation indicators of various disease monitoring time series prediction models.At the same time,this study introduces the main software commonly used for modeling,provides readers with a detailed and comprehensive introduction to the current application progress in disease monitoring time series prediction models both domestically and internationally,and provides important references for better establishing prediction and early warning models.
关键词
疾病监测/预测/时间序列/模型Key words
disease surveillance/prediction/time series/model引用本文复制引用
出版年
2024
NETL
NSTL
万方数据