登录
 机构网站
  1. 首页
  2. 情报产品
  3. 快讯详情

《LANCET，6月29日，Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid》

  • 来源专题：COVID-19科研动态监测
  • 编译者： xuwenwhlib
  • 发布时间：2020-07-05

  • Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid

    Urs Gasser, PhD

    Marcello Ienca, PhD

    James Scheibner, PhD

    Joanna Sleigh, MA

    Prof Effy Vayena, PhD

    Open AccessPublished:June 29, 2020DOI:https://doi.org/10.1016/S2589-7500(20)30137-0

    Summary

    Data collection and processing via digital public health technologies are being promoted worldwide by governments and private companies as strategic remedies for mitigating the COVID-19 pandemic and loosening lockdown measures. However, the ethical and legal boundaries of deploying digital tools for disease surveillance and control purposes are unclear, and a rapidly evolving debate has emerged globally around the promises and risks of mobilising digital tools for public health. To help scientists and policy makers to navigate technological and ethical uncertainty, we present a typology of the primary digital public health applications that are in use. These include proximity and contact tracing, symptom monitoring, quarantine control, and flow modelling. For each, we discuss context-specific risks, cross-sectional issues, and ethical concerns. Finally, recognising the need for practical guidance, we propose a navigation aid for policy makers and other decision makers for the ethical development and use of digital public health tools.

  • 原文来源：https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30137-0/fulltext
24浏览量
原文链接
相关报告

  • 《LANCET，6月29日，Applications of digital technology in COVID-19 pandemic planning and response》
    • 来源专题：COVID-19科研动态监测
    • 编译者：xuwenwhlib
    • 发布时间：2020-07-05
    • Applications of digital technology in COVID-19 pandemic planning and response Sera Whitelaw, BSc Prof Mamas A Mamas, DPhil Prof Eric Topol, MD Harriette G C Van Spall, MD Open AccessPublished:June 29, 2020DOI:https://doi.org/10.1016/S2589-7500(20)30142-4 Summary With high transmissibility and no effective vaccine or therapy, COVID-19 is now a global pandemic. Government-coordinated efforts across the globe have focused on containment and mitigation, with varying degrees of success. Countries that have maintained low COVID-19 per-capita mortality rates appear to share strategies that include early surveillance, testing, contact tracing, and strict quarantine. The scale of coordination and data management required for effective implementation of these strategies has—in most successful countries—relied on adopting digital technology and integrating it into policy and health care. This Viewpoint provides a framework for the application of digital technologies in pandemic management and response, highlighting ways in which successful countries have adopted these technologies for pandemic planning, surveillance, testing, contact tracing, quarantine, and health care.
    22浏览量
    原文链接

  • 《LANCET，3月23日，Scientific and ethical basis for social-distancing interventions against COVID-19》
    • 来源专题：COVID-19科研动态监测
    • 编译者：zhangmin
    • 发布时间：2020-03-24
    • Scientific and ethical basis for social-distancing interventions against COVID-19 Joseph A Lewnard Nathan C Lo Published:March 23, 2020DOI:https://doi.org/10.1016/S1473-3099(20)30190-0 On Dec 31, 2019, the WHO China Country Office received notice of a cluster of pneumonia cases of unknown aetiology in the Chinese city of Wuhan, Hubei province.1 The incidence of coronavirus disease 2019 (COVID-19; caused by severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) has since risen exponentially, now affecting all WHO regions. The number of cases reported to date is likely to represent an underestimation of the true burden as a result of shortcomings in surveillance and diagnostic capacity affecting case ascertainment in both high-resource and low-resource settings.2 By all scientifically meaningful criteria, the world is undergoing a COVID-19 pandemic.
    15浏览量
    原文链接