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… Read more
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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.
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
Cover
Title page
Table of Contents
Copyright
Contributors
About the editors
Preface
References
Acknowledgments
Chapter One: COVID-19: Origin, epidemiology, virology, pathogenesis, and treatment
Abstract
1: Introduction
2: Viral morphology
3: Viral pathogenesis
4: Stages of COVID-19
5: Laboratory diagnosis for screening and diagnosis of patients with COVID-19
6: Drugs used in COVID-19 till now with newer drug possibilities tried for infection
7: Potential sites for the target for vaccine and drug development
8: Conclusion
References
Chapter Two: Coronavirus reinfections: An outlook on evidences and effects
Abstract
1: Introduction
2: Coronavirus reinfection
3: Reinfection and genome sequence
4: Immunopathogenesis of Coronavirus infection
5: Reinfection and immune response
6: Severity and risk of Coronavirus reinfection
7: Management strategies and guidelines for COVID-19 reinfection
8: COVID-19 reinfection and vaccine development
9: COVID-19 waves and reinfections
10: Herd immunity and COVID-19 reinfection
11: Prevention against COVID-19 reinfection
12: Implication on COVID-19 reinfection studies
13: Conclusion
References
Chapter Three: Effect of yoga mudras in improving the health of users: A precautionary measure practice in daily life for resisting the deadly COVID-19 disease
Abstract
Acknowledgment
1: Introduction
2: Materials and methods
3: Proposed yoga health package model
4: Results and discussion
5: Conclusion
Appendix
References
Chapter Four: Blockchain: Opportunities in the healthcare sector and its uses in COVID-19
Abstract
1: Introduction
2: Chapter objectives
3: Research design
4: Blockchain technology (BCT)—An overview
5: Challenges and opportunities in the healthcare sector
6: Implementation of BC in developing and developed nations
7: Blockchain: Uses/applications in healthcare
8: Blockchain: Implementation challenges and considerations in healthcare
9: Blockchain: Fight against COVID-19 in healthcare
10: Blockchain: Future in healthcare
11: Conclusion and recommendations
References
Chapter Five: COVID-19 and its impact on cancer, HIV, and mentally ill patients
Abstract
Acknowledgments
1: Introduction: SARS-COVID-19
2: COVID-19 and cancer
3: COVID-19 and HIV
4: Effect of COVID-19 and current treatment or management strategies for mentally ill patients
5: COVID-19 and Ayurveda’s holistic lifestyle approach
6: Softwares/web tools/digital platforms used for COVID-19 management
7: Concluding remarks
References
Chapter Six: Revisiting the efficacy of policies in the Indian primary healthcare sector: Interventions and approaches during the COVID-19 pandemic
Abstract
1: Introduction
2: Methodology
3: Journey of PHC from conceptualization to the reality
4: Discussion
5: Conclusion
Glossary
References
Further reading
Chapter Seven: Benefits and use of blockchain technology to support supply chain during COVID-19
Abstract
1: Introduction
2: Introducing blockchain basic concepts
3: Supply chain explained
4: Blockchain-based model for vaccine supply chain
5: Conclusion
References
Chapter Eight: Novel coronavirus disease (COVID-19): Emergence, early infection rate, and deployment strategies for preventive solutions
Abstract
Acknowledgment
1: Introduction
2: Various epidemics and pandemics in the history of human civilization
3: Transmissibility and severity of COVID-19
4: Incubation period of COVID-19 virus
5: Symptoms of COVID-19
6: Spreading behavior of COVID-19 by PCA during the initial phase
7: Preventive measures taken by the top most affected countries to combat the COVID-19 during the first wave
8: Potential dietary remedies, herbal medicines, and allopathic therapy for COVID-19
9: Conclusions
References
Chapter Nine: Challenges and opportunities in the provision of mental health care services during the COVID-19 pandemic and beyond
Abstract
1: Introduction
2: WHO guidelines on mental health response during COVID-19 pandemic
3: The delivery of psychological services through online channels
4: Opportunities in telehealth services
5: Lessons for the future
6: Conclusions
References
Chapter Ten: Applications of machine learning approaches to combat COVID-19: A survey
Abstract
1: Introduction
2: Background
3: Applications of AI and ML in COVID-19
4: Challenges and future directions
5: Conclusions
References
Chapter Eleven: Machine learning modeling techniques and statistical projections to predict the outbreak of COVID-19 with implication to India
Abstract
1: Introduction
2: Literature survey
3: Predicting and analyzing COVID-19 outbreak
4: Prophet model to predict confirmed cases of COVID-19 with implication to India
5: Discussion and implications
6: Conclusion
References
Chapter Twelve: Lexical modeling and weighted matrices for analyses of COVID-19 outbreak
Abstract
1: Introduction
2: Related work
3: About COVID-19 diagnostic methods
4: Framework
5: Implementation result
6: Discussion
7: Conclusion
8: Future work
References
Further reading
Chapter Thirteen: Design of IoT-enabled, scalable mobile application for ASHA workers in COVID-19 data management
Abstract
1: Introduction
2: Related works
3: Application software developed by various other countries
4: Design of proposed IoT enabled device
5: Android package kit development
6: Visualization of utility of the ASHA bot app
7: View public details
8: Software and services used
9: Conclusions
References
Chapter Fourteen: Reflecting on the impact of COVID-19 on healthcare and IT sector with special emphasis on India: A collection of multifarious cases with few empirical evidences
Abstract
1: Introduction
2: Conclusion
References
Further reading
Chapter Fifteen: Modeling of cyber threat analysis and vulnerability in IoT-based healthcare systems during COVID
Abstract
1: Introduction
2: Literature review
3: Proposed model
4: Results and discussion
5: Conclusions
References
Further reading
Index
No. of pages: 466
Language: English
Published: June 18, 2022
Imprint: Academic Press
Paperback ISBN: 9780323998789
eBook ISBN: 9780323999441
AK
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
AA
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
KO
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
SG
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