Lessons from COVID-19

Lessons from COVID-19

Impact on Healthcare Systems and Technology

1st Edition - June 9, 2022

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  • Editors: Arturas Kaklauskas, Ajith Abraham, Kingsley Okoye, Shankru Guggari
  • Paperback ISBN: 9780323998789

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Lessons from COVID-19: Impact on Healthcare Systems and Technology uncovers the impact that COVID-19 has made on healthcare and technology industries. State-of-the-art case studies, empirical research, and new trends in technology-mediated solution are discussed to help inform and guide readers in understanding the effects that the COVID-19 outbreak has had across healthcare and technology industries. The book discusses challenges to identify vaccines, changes in legislation on clinical trials and re-purposing of licensed drugs, effects on primary healthcare, best practices adopted by different countries to control the pandemic, and different effects on patients within diverse age groups and comorbidities. In addition, the book covers technology-mediated solutions and infrastructures applied, digital transformations, modeling techniques, statistical projections, and the benefits and use of cloud computing and artificial intelligence. This is a valuable resource for healthcare professionals, medical doctors, researchers and graduate students from both biomedical and technological fields who are interested in learning more about the use of new technologies to fight a pandemic.

Key Features

  • Discusses the effects of COVID-19 on healthcare and technology
  • Presents case studies and state-of-the-art research and technologies to help readers effectively understand the effects of COVID-19
  • Empowers researchers to work on effective hypothesis to test the disruptions and changes that have occurred as a result of COVID-19
  • Bridges practical and theoretical gaps in terms of lessons learned during COVID-19 in the healthcare and technology sectors


Graduate students, medical doctors, policy makers, researchers on medical informatics. Data scientists, computer scientists

Table of Contents

  • PART I: Healthcare Sector
    1. History of COVID-19
    2. Problems and challenges in identifying vaccines for COVID-19
    3. Changes of legislation on clinical trials, and re-purposing of licensed drugs for the treatment of COVID-19 symptoms
    4. Effects of COVID-19 on primary health care
    5. Impact of COVID-19 on expectant parents and different stakeholders
    6. Effects of COVID-19 on doctors, medical professionals, nurses and supporting staffs of hospitals
    7. Best practises adopted by different countries to control the COVID-19 pandemic
    8. Disproportionate healthcare implications of COVID-19 due to age, ethnicity, gender, and socio-economic status
    9. How COVID-19 pandemic has affected Global healthcare and its implications for the future of Healthcare
    10. Socio-cultural and Economic effects of COVID-19 on global health care
    11. Psychological effects of COVID-19 on human beings
    12. Effects of COVID-19 on medical and clinical researchers
    13. Effects of COVID-19 on Tele-medicine, Clinical workflow, Security and Privacy Issues
    14. Effects of COVID-19 on drug manufacturing companies.
    15. Effects of COVID-19 on kids
    16. Effects of COVID-19 on the middle age and 21st century generation.
    17. Effects of COVID-19 on the healthcare of the elderly
    18. Effects of COVID-19 for people with diseases like Cancer, HIV, Mental health patients, and people with disabilities in general
    19. Health and safety best practices for use in Health environments and Public spaces during and after COVID-19

    PART II: Computing and Informatics
    20. Future research scope on COVID-19 treatment and Health informatics
    21. COVID-19 Technology-mediated solutions and infrastructures
    22. e-Health and Post-COVID-19 era
    23. Role and impact of digital technologies and mass media during COVID-19
    24. Digital transformation of the healthcare sector triggered by the Covid-19 pandemic
    25. Advances in virtual clinical learning, diagnosis, and therapy
    26. Modelling techniques and statistical projections that are used to predict the spread of the COVID-19 virus and decision making
    27. Success rates and turnaround times with COVID-19 using ICT
    28. Main enabling ICT technologies for the development of cutting-edge healthcare systems and services
    29. Effects of COVID-19 on virtual healthcare with the usage of Internet of Things (IoT) technology
    30. Benefits and use of Cloud computing to provide IT infrastructure during COVID-19
    31. Benefits and use of Edge computing to provide IT infrastructure during COVID-19
    32. Benefits and use of Artificial Intelligence (AI) to provide IT infrastructure during COVID-19
    33. Benefits and use of Big Data Management and Machine Learning techniques to provide IT infrastructure during COVID-19

Product details

  • No. of pages: 600
  • Language: English
  • Copyright: © Academic Press 2022
  • Published: June 9, 2022
  • Imprint: Academic Press
  • Paperback ISBN: 9780323998789

About the Editors

Arturas Kaklauskas

A. Kaklauskas is a professor at Vilnius Gediminas Technical University, in Lithuania; Member of the Research Council of Lithuania; Member of the Science Europe working group on Data Sharing and Supporting Infrastructures; Head of the Department of Construction Management and Property; member of the Lithuanian Academy of Sciences; editor-in-chief of Journal of Civil Engineering and Management; editor of Engineering Applications of Artificial Intelligence; and associate editor of Ecological Indicators. He contributed to nine Framework and five Horizon 2020 program projects and participated in over 30 other projects in the EU, US, Africa. and Asia. His publications include nine books and 150 papers. His areas of interest include affective computing; intelligent tutoring systems; affective intelligent tutoring systems; massive open online courses (MOOCS); affective internet of things; smart built environment; intelligent event prediction; opinion mining; intelligent decision support systems; life cycle analyses of built environments; big data and text analytics.

Affiliations and Expertise

Professor, Vilnius Gediminas Technical University, Vilnius, Lithuania

Ajith Abraham

Dr. Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), a Not-for-Profit Scientific Network for Innovation and Research Excellence connecting Industry and Academia. The Network with HQ in Seattle, USA has currently more than 1,500 scientific members from over 105 countries. As an Investigator / Co-Investigator, he has won research grants worth over 100+ Million US$. Currently he works as a Professor of Artificial Intelligence in Innopolis University, Russia and is a Chairholder of the Yayasan Tun Ismail Mohamed Ali Professorial Chair in Artificial Intelligence of UCSI, Malaysia. Dr. Abraham works in a multi-disciplinary environment and he has authored / coauthored more than 1,400+ research publications out of which there are 100+ books covering various aspects of Computer Science. One of his books was translated to Japanese and few other articles were translated to Russian and Chinese. Dr. Abraham has more than 45,500+ academic citations (h-index of 100 as per google scholar). He has given more than 150 plenary lectures and conference tutorials (in 20+ countries). Since 2008, Dr. Abraham was the Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (which has over 200+ members) during 2008-2021 and served as a Distinguished Lecturer of IEEE Computer Society representing Europe (2011-2013). Dr. Abraham was the editor-in-chief of Engineering Applications of Artificial Intelligence (EAAI) during 2016-2021 and is currently serving / served the editorial board of over 15 International Journals indexed by Thomson ISI. Dr. Abraham received Ph.D. degree in Computer Science from Monash University, Melbourne, Australia (2001) and a Master of Science Degree from Nanyang Technological University, Singapore (1998).

Affiliations and Expertise

Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn, WA, United States

Kingsley Okoye

Kingsley Okoye received his PhD in Software Engineering from the University of East London, UK. He is an MIET member at the Institution of Engineering and Technology, UK, and a Graduate Member of the IEEE. He is a devoted researcher to Industry and Academia in areas such as Data Science, Machine Learning, Artificial Intelligence, Big Data and Advanced Analytics, Software Development and Programming, and Business Process Management. Kingsley is a Data Architect in the Writing Lab of Tecnologico de Monterrey. He is also a member of the Machine Intelligence Research Labs, USA, and a member of the IEEE SMCS Technical Committee (TC) on Soft Computing. His Research interests includes: Process Mining and Automation, Learning Analytics and Systems Design, Semantic Web Technologies, Knowledge Engineering and Data Management, Computer Education, Educational Innovation, Internet Applications and Ontologies.

Affiliations and Expertise

Data Architect, Writing Lab of Tecnológico de Monterrey, Monterrey, Nuevo Leon, Mexico

Shankru Guggari

Shankru Guggari is a PhD in computer science and engineering currently working on building robust classification techniques. His areas of interest are in recognition, IOT, and machine learning. Dr. Guggari has published research works in international conferences and reputed journals such as Elsevier and Springer, to name a few, and has more than four years industry and two years academic research experience. He is currently as serving as an editor for two edited books (Elsevier, Taylor, and Francis publishers). He has delivered various technical talks in different platforms. He also served as guest editor for few special issues related to AI and ML domains.

Affiliations and Expertise

Doctoral Candidate, B.M.S. College of Engineering, Bangalore, Karnataka, India

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