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      Digitalisation and COVID-19: The Perfect Storm


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          “A ship in the harbour is safe, but that is not what ships are built for,” observed that sage 19th century philosopher William Shedd. In other words, technology of high potential is of little value if the potential is not exploited. As the shape of 2020 is increasingly defined by the coronavirus pandemic, digitalisation is like a ship loaded with technology that has a huge capacity for transforming mankind's combat against infectious disease. But it is still moored safely in harbour. Instead of sailing bravely into battle, it remains at the dockside, cowering from the storm beyond the breakwaters. Engineers and fitters constantly fine-tune it, and its officers and deckhands perfect their operating procedures, but that promise is unfulfilled, restrained by the hesitancy and indecision of officialdom. Out there, the seas of the pandemic are turbulent and uncharted, and it is impossible to know in advance everything of the other dangers that may lurk beyond those cloudy horizons. However, the more noble course is for orders to be given to complete the preparations, to cast off and set sail, and to join other vessels crewed by valiant healthcare workers and tireless researchers, already deeply engaged in a rescue mission for the whole of the human race. It is the destiny of digitalisation to navigate those oceans alongside other members of that task force, and the hour of destiny has arrived. This article focuses on the potential enablers and recommendation to maximise learnings during the era of COVID-19.

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          Most cited references28

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          Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges

          Highlights • Emergence of 2019 novel coronavirus (2019-nCoV) in China has caused a large global outbreak and major public health issue. • At 9 February 2020, data from the WHO has shown >37 000 confirmed cases in 28 countries (>99% of cases detected in China). • 2019-nCoV is spread by human-to-human transmission via droplets or direct contact. • Infection estimated to have an incubation period of 2–14 days and a basic reproduction number of 2.24–3.58. • Controlling infection to prevent spread of the 2019-nCoV is the primary intervention being used.
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            Virtually Perfect? Telemedicine for Covid-19

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              Immune responses in COVID-19 and potential vaccines: Lessons learned from SARS and MERS epidemic

              As the world is witnessing the epidemic of COVID-19, a disease caused by a novel coronavirus, SARS-CoV-2, emerging genetics and clinical evidences suggest a similar path to those of SARS and MERS. The rapid genomic sequencing and open access data, together with advanced vaccine technology, are expected to give us more knowledge on the pathogen itself, including the host immune response as well as the plan for therapeutic vaccines in the near future. This review aims to provide a comparative view among SARS-CoV, MERS-CoV and the newly epidemic SARS-CoV-2, in the hope to gain a better understanding of the host-pathogen interaction, host immune responses, and the pathogen immune evasion strategies. This predictive view may help in designing an immune intervention or preventive vaccine for COVID-19 in the near future.

                Author and article information

                Biomed Hub
                Biomed Hub
                Biomedicine Hub
                S. Karger AG (Allschwilerstrasse 10, P.O. Box · Postfach · Case postale, CH–4009, Basel, Switzerland · Schweiz · Suisse, Phone: +41 61 306 11 11, Fax: +41 61 306 12 34, karger@karger.com )
                Sep-Dec 2020
                17 September 2020
                17 September 2020
                : 5
                : 3
                : 1341-1363
                [1] aEuropean Alliance for Personalised Medicine, Brussels, Belgium
                [2] bIZY Capital, London, United Kingdom
                [3] cDepartment of Internal Medicine III and Comprehensive Cancer Centre Munich, University Hospital Munich, Munich, Germany
                [4] dThe European Institute for Innovation through Health Data (i-HD), Gent, Belgium
                [5] eCIHR Institute of Genetics, Ottawa, Ontario, Canada
                [6] fIntel, Brussels, Belgium
                [7] gEATRIS, Amsterdam, The Netherlands
                [8] hDepartment of Molecular and Cellular Engineering, Jacob Institute of Biotechnology and Bioengineering, Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Prayagraj, India
                [9] iDepartment of Genetics and Cell Biology, Institute for Public Health Genomics, GROW School of Oncology and Developmental Biology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
                [10] jVilnius University Hospital Santaros Clinics, Vilnius, Lithuania
                [11] kSezione di Igiene, Dipartimento Universitario Scienze della Vita e Sanità Pubblica, Università Cattolica del Sacro Cuore, Rome, Italy
                [12] lDepartment of Woman and Child Health and Public Health − Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
                [13] mEuropean Commission, Luxembourg City, Luxembourg
                Author notes
                *Denis Horgan, European Alliance for Personalised Medicine, Rue de l'Aqueduc 88, BE–1050 Brussels (Belgium), denishorgan@ 123456euapm.eu
                Copyright © 2020 by S. Karger AG, Basel
                : 31 July 2020
                : 24 August 2020
                : 2020
                Page count
                Figures: 5, References: 104, Pages: 23
                Position Statement

                artificial intelligence,big data,diagnostics,digital health,european commission,european health data space,genomics,innovation,machine learning,million european genome alliance,personalised healthcare,regulatory framework,technology


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