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基于互联网的监测系统与传染病预测:对过去 10 年的最新回顾及新冠疫情带来的启示。

Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic.

机构信息

Ecosystem Change and Population Health (ECAPH) Research Group, School of Public Health and Social Work, Queensland University of Technology (QUT), Brisbane, Australia.

Communicable Diseases Branch, Queensland Health, Brisbane, Australia.

出版信息

J Epidemiol Glob Health. 2024 Sep;14(3):645-657. doi: 10.1007/s44197-024-00272-y. Epub 2024 Aug 14.

DOI:10.1007/s44197-024-00272-y
PMID:39141074
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11442909/
Abstract

The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing adoption of smart devices, increased availability of Artificial Intelligence (AI), alongside environmental pressures including climate and land use change contributing to increased threat and spread of pandemics and emerging infectious diseases. With the increasing burden of infectious diseases and the COVID-19 pandemic, the need for developing novel technologies and integrating internet-based data approaches to improving infectious disease surveillance is greater than ever. In this systematic review, we searched the scientific literature for research on internet-based or digital surveillance for influenza, dengue fever and COVID-19 from 2013 to 2023. We have provided an overview of recent internet-based surveillance research for emerging infectious diseases (EID), describing changes in the digital landscape, with recommendations for future research directed at public health policymakers, healthcare providers, and government health departments to enhance traditional surveillance for detecting, monitoring, reporting, and responding to influenza, dengue, and COVID-19.

摘要

过去十年,随着先进计算能力的发展、智能设备的广泛应用、人工智能(AI)的可用性提高,以及包括气候和土地利用变化在内的环境压力的增加,导致传染病大流行和新发传染病的威胁和传播加剧,基于互联网的传染病监测技术取得了重大进展和增长。随着传染病负担的增加和 COVID-19 大流行,开发新技术和整合基于互联网的数据方法以改善传染病监测的需求比以往任何时候都更加迫切。在这项系统评价中,我们从 2013 年至 2023 年,在科学文献中搜索了关于流感、登革热和 COVID-19 的基于互联网或数字监测的研究。我们提供了新兴传染病(EID)基于互联网监测的最新研究概述,描述了数字环境的变化,并为公共卫生政策制定者、医疗保健提供者和政府卫生部门提出了未来的研究建议,以加强传统监测,以检测、监测、报告和应对流感、登革热和 COVID-19。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/7db6af4b8d2c/44197_2024_272_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/4119dc977e4a/44197_2024_272_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/5a37ff8634f9/44197_2024_272_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/199df5554e89/44197_2024_272_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/7db6af4b8d2c/44197_2024_272_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/4119dc977e4a/44197_2024_272_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/5a37ff8634f9/44197_2024_272_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/199df5554e89/44197_2024_272_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37fb/11442909/7db6af4b8d2c/44197_2024_272_Fig4_HTML.jpg

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