Hossain Md Arafat, Brito-Rodriguez Barbara, Sedger Lisa M, Canning John
Department of Electrical and Electronic EngineeringKhulna University of Engineering & Technology Khulna 9203 Bangladesh.
Faculty of Sciencei3 Institute, University of Technology Sydney (UTS) Sydney NSW 2007 Australia.
IEEE Access. 2021 Dec 6;9:163716-163734. doi: 10.1109/ACCESS.2021.3133417. eCollection 2021.
The SARS-Coronavirus-2 (SARS-CoV-2) infectious disease, COVID-19, has spread rapidly, resulting in a global pandemic with significant mortality. The combination of early diagnosis via rapid screening, contact tracing, social distancing and quarantine has helped to control the pandemic. The absence of real time response and diagnosis is a crucial technology shortfall and is a key reason why current contact tracing methods are inadequate to control spread. In contrast, current information technology combined with a new generation of near-real time tests offers consumer-engaged smartphone-based "lab-in-a-phone" internet-of-things (IoT) connected devices that provide increased pandemic monitoring. This review brings together key aspects required to create an entire global diagnostic ecosystem. Cross-disciplinary understanding and integration of both mechanisms and technologies for effective detection, incidence mapping and disease containment in near real-time is summarized. Available measures to monitor and/or sterilize surfaces, next-generation laboratory and smartphone-based diagnostic approaches can be brought together and networked for instant global monitoring that informs Public Health policy. Cloud-based analysis enabling real-time mapping will enable future pandemic control, drive the suppression and elimination of disease spread, saving millions of lives globally. A new paradigm is introduced - scaled and multiple diagnostics for mapping and spreading of a pandemic rather than traditional accumulation of individual measurements. This can do away with the need for ultra-precise and ultra-accurate analysis by taking mass measurements that can relax tolerances and build resilience through networked analytics and informatics, the basis for novel swarm diagnostics. These include addressing ethical standards, local, national and international collaborative engagement, multidisciplinary and analytical measurements and standards, and data handling and storage protocols.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引发的传染病COVID-19迅速蔓延，导致全球大流行并造成重大死亡。通过快速筛查、接触者追踪、社交距离和隔离进行早期诊断的综合措施有助于控制疫情。缺乏实时响应和诊断是一项关键的技术短板，也是当前接触者追踪方法不足以控制传播的关键原因。相比之下，当前的信息技术与新一代近实时检测相结合，提供了基于消费者参与的、与物联网（IoT）相连的智能手机“手机实验室”设备，可加强疫情监测。本综述汇集了创建全球诊断生态系统所需的关键要素。总结了跨学科的理解以及有效检测、发病率测绘和近实时疾病控制的机制与技术整合。可将用于监测和/或消毒表面的现有措施、下一代实验室诊断方法和基于智能手机的诊断方法整合并联网，以实现即时全球监测，为公共卫生政策提供依据。基于云的分析实现实时测绘将助力未来的疫情控制，推动抑制和消除疾病传播，在全球范围内挽救数百万人的生命。引入了一种新范式——大规模、多重诊断以绘制疫情地图和传播情况，而非传统的个体测量累积。通过进行大规模测量，可放宽公差并通过联网分析和信息学建立弹性，从而无需超精确和超准确的分析，这是新型群体诊断的基础。这些要素包括解决道德标准、地方、国家和国际合作参与、多学科和分析测量及标准，以及数据处理和存储协议等问题。
