Fallatah Deema Ibrahim, Adekola Hafeez Aderinsayo
Department of Clinical Laboratory Sciences, Prince Sattam bin Abdulaziz University, Saudi Arabia.
Department of Molecular Biology and Biotechnology, Nigerian Institute of Medical Research, Nigeria.
Infect Prev Pract. 2024 Jun 29;6(3):100382. doi: 10.1016/j.infpip.2024.100382. eCollection 2024 Sep.
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.
数字流行病学是调查疾病相关模式(包括社会和临床模式)动态变化以及这些流行病学趋势成因的过程。利用来自各种数字来源的大数据的数字流行病学,已成为早期检测和监测病毒爆发的一种可行方法。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。研究人员可以使用搜索引擎查询、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爆发。然而,必须解决数据质量、隐私问题和数据互操作性,以最大限度地提高数字流行病学的有效性。随着全球传染病格局的演变,整合数字流行病学对于改善大流行防范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改善全球健康状况,并在病毒爆发时拯救生命。