• 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

流感病毒:追踪、预测和预报。

Influenza Virus: Tracking, Predicting, and Forecasting.

机构信息

World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; email:

出版信息

Annu Rev Public Health. 2021 Apr 1;42:43-57. doi: 10.1146/annurev-publhealth-010720-021049. Epub 2021 Dec 21.

DOI:10.1146/annurev-publhealth-010720-021049
PMID:33348997
Abstract

Influenza is a common respiratory infection that causes considerable morbidity and mortality worldwide each year. In recent years, along with the improvement in computational resources, there have been a number of important developments in the science of influenza surveillance and forecasting. Influenza surveillance systems have been improved by synthesizing multiple sources of information. Influenza forecasting has developed into an active field, with annual challenges in the United States that have stimulated improved methodologies. Work continues on the optimal approaches to assimilating surveillance data and information on relevant driving factors to improve estimates of the current situation (nowcasting) and to forecast future dynamics.

摘要

流感是一种常见的呼吸道感染,每年在全球范围内都会导致相当高的发病率和死亡率。近年来,随着计算资源的提高,流感监测和预测领域有了一些重要的发展。通过综合多种信息来源,流感监测系统得到了改进。流感预测已经发展成为一个活跃的领域,美国每年都会面临挑战,这刺激了改进方法的出现。目前,人们继续致力于寻找最佳方法来整合监测数据和相关驱动因素的信息,以改善对当前情况(实时预测)的估计,并预测未来的动态。

相似文献

1
Influenza Virus: Tracking, Predicting, and Forecasting.流感病毒:追踪、预测和预报。
Annu Rev Public Health. 2021 Apr 1;42:43-57. doi: 10.1146/annurev-publhealth-010720-021049. Epub 2021 Dec 21.
2
Optimal multi-source forecasting of seasonal influenza.季节性流感的最优多源预测。
PLoS Comput Biol. 2018 Sep 4;14(9):e1006236. doi: 10.1371/journal.pcbi.1006236. eCollection 2018 Sep.
3
Forecasting influenza-like illness dynamics for military populations using neural networks and social media.利用神经网络和社交媒体预测军队人群中流感样疾病的动态。
PLoS One. 2017 Dec 15;12(12):e0188941. doi: 10.1371/journal.pone.0188941. eCollection 2017.
4
Forecasting the spatial transmission of influenza in the United States.预测美国流感的空间传播。
Proc Natl Acad Sci U S A. 2018 Mar 13;115(11):2752-2757. doi: 10.1073/pnas.1708856115. Epub 2018 Feb 26.
5
Forecasting the 2013-2014 influenza season using Wikipedia.利用维基百科预测2013 - 2014年流感季节。
PLoS Comput Biol. 2015 May 14;11(5):e1004239. doi: 10.1371/journal.pcbi.1004239. eCollection 2015 May.
6
Type- and Subtype-Specific Influenza Forecast.特定类型和亚型的流感预测。
Am J Epidemiol. 2017 Mar 1;185(5):395-402. doi: 10.1093/aje/kww211.
7
Evolution-informed forecasting of seasonal influenza A (H3N2).基于进化信息的季节性流感 A(H3N2)预测。
Sci Transl Med. 2017 Oct 25;9(413). doi: 10.1126/scitranslmed.aan5325.
8
CDC National Health Report: leading causes of morbidity and mortality and associated behavioral risk and protective factors--United States, 2005-2013.美国疾病控制与预防中心国家健康报告:2005 - 2013年美国发病和死亡的主要原因以及相关行为风险和保护因素
MMWR Suppl. 2014 Oct 31;63(4):3-27.
9
Collaborative efforts to forecast seasonal influenza in the United States, 2015-2016.
Sci Rep. 2019 Jan 24;9(1):683. doi: 10.1038/s41598-018-36361-9.
10
Nowcasting (Short-Term Forecasting) of Influenza Epidemics in Local Settings, Sweden, 2008-2019.2008-2019 年瑞典局部地区流感疫情的实时预测(短期预测)。
Emerg Infect Dis. 2020 Nov;26(11):2669-2677. doi: 10.3201/eid2611.200448.

引用本文的文献

1
Epidemiological characteristics of influenza after COVID-19 pandemic in Zhejiang province, China.中国浙江省新冠疫情大流行后流感的流行病学特征
BMC Infect Dis. 2025 Sep 2;25(1):1090. doi: 10.1186/s12879-025-11514-0.
2
Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.中国季节性流感基于概率的早期预警:模型开发研究
JMIR Med Inform. 2025 Aug 6;13:e73631. doi: 10.2196/73631.
3
Epidemiological intricacies of respiratory pathogens: a single-center study on infection dynamics in Beijing, 2023-2024.
呼吸道病原体的流行病学复杂性:2023 - 2024年北京感染动态的单中心研究
Front Public Health. 2025 Jun 26;13:1581815. doi: 10.3389/fpubh.2025.1581815. eCollection 2025.
4
Retrospective Single-Center Study on the Epidemiological Characteristics of Influenza B Infections in Korea (2007-2024): Analysis of Sex, Age, and Seasonal Patterns.韩国乙型流感感染流行病学特征的回顾性单中心研究(2007 - 2024年):性别、年龄及季节性模式分析
Microorganisms. 2025 May 16;13(5):1141. doi: 10.3390/microorganisms13051141.
5
A Novel Grammar-Based Approach for Patients' Symptom and Disease Diagnosis Information Dissemination to Maintain Confidentiality and Information Integrity.一种基于语法的新型方法,用于患者症状和疾病诊断信息的传播,以维护保密性和信息完整性。
Bioengineering (Basel). 2024 Dec 13;11(12):1265. doi: 10.3390/bioengineering11121265.
6
Forecasting influenza epidemics in China using transmission dynamic model with absolute humidity.利用包含绝对湿度的传播动力学模型预测中国的流感流行情况。
Infect Dis Model. 2024 Aug 10;10(1):50-59. doi: 10.1016/j.idm.2024.08.003. eCollection 2025 Mar.
7
Forecasting of influenza activity and associated hospital admission burden and estimating the impact of COVID-19 pandemic on 2019/20 winter season in Hong Kong.预测流感活动及相关住院负担,并估计 COVID-19 大流行对香港 2019/20 年冬季的影响。
PLoS Comput Biol. 2024 Jul 31;20(7):e1012311. doi: 10.1371/journal.pcbi.1012311. eCollection 2024 Jul.
8
Predicting seasonal influenza outbreaks with regime shift-informed dynamics for improved public health preparedness.利用体制转变信息动力学预测季节性流感爆发,以提高公共卫生准备。
Sci Rep. 2024 Jun 3;14(1):12698. doi: 10.1038/s41598-024-63573-z.
9
Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models.中国福州流感爆发预测:预测模型的比较分析。
BMC Public Health. 2024 May 25;24(1):1399. doi: 10.1186/s12889-024-18583-x.
10
Transmission restriction and genomic evolution co-shape the genetic diversity patterns of influenza A virus.传播限制和基因组进化共同塑造了甲型流感病毒的遗传多样性模式。
Virol Sin. 2024 Aug;39(4):525-536. doi: 10.1016/j.virs.2024.02.005. Epub 2024 Feb 27.