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      Transforming healthcare through a digital revolution: A review of digital healthcare technologies and solutions

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          Abstract

          The COVID-19 pandemic has put a strain on the entire global healthcare infrastructure. The pandemic has necessitated the re-invention, re-organization, and transformation of the healthcare system. The resurgence of new COVID-19 virus variants in several countries and the infection of a larger group of communities necessitate a rapid strategic shift. Governments, non-profit, and other healthcare organizations have all proposed various digital solutions. It's not clear whether these digital solutions are adaptable, functional, effective, or reliable. With the disease becoming more and more prevalent, many countries are looking for assistance and implementation of digital technologies to combat COVID-19. Digital health technologies for COVID-19 pandemic management, surveillance, contact tracing, diagnosis, treatment, and prevention will be discussed in this paper to ensure that healthcare is delivered effectively. Artificial Intelligence (AI), big data, telemedicine, robotic solutions, Internet of Things (IoT), digital platforms for communication (DC), computer vision, computer audition (CA), digital data management solutions (blockchain), digital imaging are premiering to assist healthcare workers (HCW's) with solutions that include case base surveillance, information dissemination, disinfection, and remote consultations, along with many other such interventions.

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          Most cited references33

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          Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

          Summary Background An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus 2 (SARS-CoV-2) started in December, 2019, in Wuhan, China. Information about critically ill patients with SARS-CoV-2 infection is scarce. We aimed to describe the clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia. Methods In this single-centered, retrospective, observational study, we enrolled 52 critically ill adult patients with SARS-CoV-2 pneumonia who were admitted to the intensive care unit (ICU) of Wuhan Jin Yin-tan hospital (Wuhan, China) between late December, 2019, and Jan 26, 2020. Demographic data, symptoms, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between survivors and non-survivors. The primary outcome was 28-day mortality, as of Feb 9, 2020. Secondary outcomes included incidence of SARS-CoV-2-related acute respiratory distress syndrome (ARDS) and the proportion of patients requiring mechanical ventilation. Findings Of 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adult patients were included. The mean age of the 52 patients was 59·7 (SD 13·3) years, 35 (67%) were men, 21 (40%) had chronic illness, 51 (98%) had fever. 32 (61·5%) patients had died at 28 days, and the median duration from admission to the intensive care unit (ICU) to death was 7 (IQR 3–11) days for non-survivors. Compared with survivors, non-survivors were older (64·6 years [11·2] vs 51·9 years [12·9]), more likely to develop ARDS (26 [81%] patients vs 9 [45%] patients), and more likely to receive mechanical ventilation (30 [94%] patients vs 7 [35%] patients), either invasively or non-invasively. Most patients had organ function damage, including 35 (67%) with ARDS, 15 (29%) with acute kidney injury, 12 (23%) with cardiac injury, 15 (29%) with liver dysfunction, and one (2%) with pneumothorax. 37 (71%) patients required mechanical ventilation. Hospital-acquired infection occurred in seven (13·5%) patients. Interpretation The mortality of critically ill patients with SARS-CoV-2 pneumonia is considerable. The survival time of the non-survivors is likely to be within 1–2 weeks after ICU admission. Older patients (>65 years) with comorbidities and ARDS are at increased risk of death. The severity of SARS-CoV-2 pneumonia poses great strain on critical care resources in hospitals, especially if they are not adequately staffed or resourced. Funding None.
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            The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review

            The COVID-19 pandemic has resulted in over 1.4 million confirmed cases and over 83,000 deaths globally. It has also sparked fears of an impending economic crisis and recession. Social distancing, self-isolation and travel restrictions forced a decrease in the workforce across all economic sectors and caused many jobs to be lost. Schools have closed down, and the need of commodities and manufactured products has decreased. In contrast, the need for medical supplies has significantly increased. The food sector has also seen a great demand due to panic-buying and stockpiling of food products. In response to this global outbreak, we summarise the socio-economic effects of COVID-19 on individual aspects of the world economy.
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              Prevalence of Asymptomatic SARS-CoV-2 Infection

              Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly throughout the world since the first cases of coronavirus disease 2019 (COVID-19) were observed in December 2019 in Wuhan, China. It has been suspected that infected persons who remain asymptomatic play a significant role in the ongoing pandemic, but their relative number and effect have been uncertain. The authors sought to review and synthesize the available evidence on asymptomatic SARS-CoV-2 infection. Asymptomatic persons seem to account for approximately 40% to 45% of SARS-CoV-2 infections, and they can transmit the virus to others for an extended period, perhaps longer than 14 days. Asymptomatic infection may be associated with subclinical lung abnormalities, as detected by computed tomography. Because of the high risk for silent spread by asymptomatic persons, it is imperative that testing programs include those without symptoms. To supplement conventional diagnostic testing, which is constrained by capacity, cost, and its one-off nature, innovative tactics for public health surveillance, such as crowdsourcing digital wearable data and monitoring sewage sludge, might be helpful.
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                Author and article information

                Contributors
                Journal
                Front Digit Health
                Front Digit Health
                Front. Digit. Health
                Frontiers in Digital Health
                Frontiers Media S.A.
                2673-253X
                04 August 2022
                2022
                : 4
                : 919985
                Affiliations
                [1] 1Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal , Karnataka, India
                [2] 2iTRUE (International Training and Research in Uro-Oncology and Endourology) Group, Manipal , Karnataka, India
                [3] 3Department of Urology, Father Muller Medical College, Mangalore , Karnataka, India
                [4] 4Department of Mechanical Engineering, University of Moratuwa , Moratuwa, Sri Lanka
                [5] 5Department of Oral and Maxillofacial Surgery, Radboud University , Nijmegen, Netherlands
                [6] 6Department of Oral Medicine and Radiology, Manipal College of Dental Sciences, Manipal, Manipal Academy of Higher Education, Manipal , Karnataka, India
                [7] 7Robotics and Urooncology, Max Hospital and Max Institute of Cancer Care , New Delhi, India
                [8] 8Kasturba Medical College, Manipal Academy of Higher Education, Manipal , Karnataka, India
                [9] 9Department of Urology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal , Karnataka, India
                [10] 10Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal , Karnataka, India
                [11] 11Frontline Hospital and Research Centre, Trichy , Tamil Nadu, India
                [12] 12Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal , Karnataka, India
                [13] 13Department of Urology, Freeman Hospital , Newcastle upon Tyne, United Kingdom
                [14] 14Department of Urology, Jagiellonian University in Krakow , Kraków, Poland
                [15] 15Department of Urology, University Hospital Southampton NHS Trust , Southampton, United Kingdom
                Author notes

                Edited by: Giovanni Ferrara, University of Alberta, Canada

                Reviewed by: Saeed Hamood Alsamhi, Ibb University, Yemen

                *Correspondence: B. M. Zeeshan Hameed zeeshanhameedbm@ 123456gmail.com
                Dasharathraj K. Shetty raja.shetty@ 123456manipal.edu

                This article was submitted to Health Technology Implementation, a section of the journal Frontiers in Digital Health

                Article
                10.3389/fdgth.2022.919985
                9385947
                35990014
                2b1887e1-95e2-4f08-abe8-554f2e9d840b
                Copyright © 2022 Naik, Hameed, Sooriyaperakasam, Vinayahalingam, Patil, Smriti, Saxena, Shah, Ibrahim, Singh, Karimi, Naganathan, Shetty, Rai, Chlosta and Somani.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 16 May 2022
                : 08 July 2022
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 74, Pages: 0, Words: 6120
                Categories
                Digital Health
                Mini Review

                healthcare,telemedicine,digital healthcare,artificial intelligence,blockchain

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