数字流行病学:利用大数据及早发现和监测病毒爆发

IF 1.8 Q3 INFECTIOUS DISEASES
Deema Ibrahim Fallatah , Hafeez Aderinsayo Adekola
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引用次数: 0

摘要

数字流行病学是调查与疾病相关的社会和临床模式的动态以及这些流行病学趋势的原因的过程。数字流行病学利用各种数字来源的大数据,已成为早期发现和监测病毒爆发的可行方法。本综述概述了数字流行病学,强调其在及时发现传染病爆发方面的重要性。研究人员可利用搜索引擎查询、社交媒体趋势和数字健康记录等数字数据源实时发现和跟踪疫情。然而,要最大限度地发挥数字流行病学的功效,必须解决数据质量、隐私问题和数据互操作性等问题。随着全球传染病态势的演变,整合数字流行病学对于改进大流行病防备和应对工作至关重要。将数字流行病学纳入常规监测系统有可能在病毒爆发时改善全球健康状况并挽救生命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital epidemiology: harnessing big data for early detection and monitoring of viral outbreaks

Digital epidemiology is the process of investigating the dynamics of disease-related patterns, both social and clinical, as well as the causes of these trends in epidemiology. Digital epidemiology, utilising big data from a variety of digital sources, has emerged as a viable method for early detection and monitoring of viral outbreaks. The present review gives an overview of digital epidemiology, emphasising its importance in the timely detection of infectious disease outbreaks. Researchers may discover and track outbreaks in real time using digital data sources such as search engine queries, social media trends, and digital health records. However, data quality, concerns about privacy, and data interoperability must be addressed to maximise the effectiveness of digital epidemiology. As the global landscape of infectious diseases evolves, integrating digital epidemiology becomes critical to improving pandemic preparedness and response efforts. Integrating digital epidemiology into routine monitoring systems has the potential to improve global health outcomes and save lives in the event of viral outbreaks.

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来源期刊
Infection Prevention in Practice
Infection Prevention in Practice Medicine-Public Health, Environmental and Occupational Health
CiteScore
4.80
自引率
0.00%
发文量
58
审稿时长
61 days
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