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10.1038/s41591-020-1011-4

http://scihub22266oqcxt.onion/10.1038/s41591-020-1011-4
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32770165!ä!32770165

suck abstract from ncbi


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pmid32770165      Nat+Med 2020 ; 26 (8): 1183-1192
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  • Digital technologies in the public-health response to COVID-19 #MMPMID32770165
  • Budd J; Miller BS; Manning EM; Lampos V; Zhuang M; Edelstein M; Rees G; Emery VC; Stevens MM; Keegan N; Short MJ; Pillay D; Manley E; Cox IJ; Heymann D; Johnson AM; McKendry RA
  • Nat Med 2020[Aug]; 26 (8): 1183-1192 PMID32770165show ga
  • Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases.
  • |*Population Surveillance[MESH]
  • |Betacoronavirus/pathogenicity[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/epidemiology/*prevention & control/virology[MESH]
  • |Humans[MESH]
  • |Machine Learning[MESH]
  • |Natural Language Processing[MESH]
  • |Pandemics/prevention & control/*statistics & numerical data[MESH]
  • |Pneumonia, Viral/epidemiology/*prevention & control/virology[MESH]
  • |Privacy[MESH]
  • |Public Health/*statistics & numerical data[MESH]


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