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COVID-19: Origin, Detection and Impact Analysis Using Artificial Intelligence Computational Techniques [Kõva köide]

, , (Pantnagar, College of Technology, G.B. Pant University of Agriculture and Technology, Rudrapui, Uttarakhand, India), ,
  • Formaat: Hardback, 510 pages, kõrgus x laius: 254x178 mm, kaal: 1319 g, 70 Tables, black and white; 209 Line drawings, black and white; 41 Halftones, black and white; 250 Illustrations, black and white
  • Ilmumisaeg: 18-Aug-2021
  • Kirjastus: CRC Press
  • ISBN-10: 0367674661
  • ISBN-13: 9780367674663
  • Formaat: Hardback, 510 pages, kõrgus x laius: 254x178 mm, kaal: 1319 g, 70 Tables, black and white; 209 Line drawings, black and white; 41 Halftones, black and white; 250 Illustrations, black and white
  • Ilmumisaeg: 18-Aug-2021
  • Kirjastus: CRC Press
  • ISBN-10: 0367674661
  • ISBN-13: 9780367674663

This book highlights progress in terms of Virus Biology and Infection Detection, Prevention, and Control, along with Screening, Testing, and Detection Techniques, that will provide learners and researchers (from basic to advanced) with the most innovative computer-driven methodologies for the fight against COVID-19. In addition, this book also covers the Pre- and Post-Impact of the COVID-19 Pandemic Crisis that will definitely provide useful content for researchers to think broadly about the analytical areas affected by COVID-19. This ultimately shows different paths to the same destination to help understand the nature of the COVID-19 pandemic and how to avoid it in the future.



This book will highlight progress in terms of Virus Biology, Infection Detection, Prevention, and Control, along with Screening, Testing, and Detection Techniques that will provide learners and researchers (basic to advanceD) with the most innovative computer-driven methodologies for the fight against COVID-19.

Authors xvii
PART I Origin and Background of COVID-19
Chapter 1 Introduction to Emerging Respiratory Viruses with Coronavirus Disease (COVID-19)
3(44)
Introduction
3(1)
New and Newly Recognized Respiratory Viruses
4(7)
Influenza Viruses
4(1)
H1N1 Influenza
5(1)
H2N2 Influenza
5(1)
Avian Influenza (AI)
5(1)
A(H7N9) Virus
6(1)
A(H5N1) Virus
6(1)
Other AI Viruses
6(2)
Hantavirus
8(1)
Human Metapneumovirus (HMPV)
8(1)
Bocavirus
9(1)
Coronavirus
9(1)
HCoV-229E and HCoV-OC43
10(1)
Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)
10(1)
Middle East Respiratory Syndrome Coronavirus (MERS-CoV)
11(1)
SARS-CoV-2
11(1)
Timeline of the Emerging Viruses
11(3)
SARS-CoV-2
14(8)
Current Worldwide Scenario of SARS-CoV-2
14(2)
Time Line of the Outbreak
16(3)
Emergence of Coronavirus (SARS-CoV-2)
19(3)
Compression of Coronaviruses in Humans--SARS-CoV, MERS-CoV and COVID-19
22(3)
Prevention, Control, and Management Strategies from SARS-CoV-2
25(13)
Containment Strategies for SARS-CoV-2: Isolation, Quarantine
25(1)
Principles of Modern Quarantine
26(2)
Computational Technique of Analysis Effect of Containment Strategies
28(1)
SIR Model for Pandemics
28(3)
SIQR Model
31(2)
SEIR Model
33(2)
SEIRS Model
35(1)
Additional Preventions Tips for Community
36(1)
Case and Contact Management
37(1)
Community Containment
37(1)
Notes
38(1)
References
39(8)
Chapter 2 The Origin Molecular Structure, Function, and Evolution Insights of COVID-19: Morphogenesis and Spike Proteins
47(64)
Introduction
47(2)
Emergence of SARS-CoV and SARS-CoV-2
49(2)
Classification of Coronaviruses
51(2)
Key Features and Entry Mechanism of Human Coronaviruses
53(2)
Morphology, Genomic Structure, and Its Variation of SARS-CoV-2
55(7)
Genome Sequencing
55(1)
Genome Structure
55(2)
Accessory Proteins
57(1)
Structural Proteins of Viral
58(1)
S Protein
58(2)
E Protein
60(1)
M Protein
60(1)
N Protein
61(1)
Structure, Function, Antigenicity, and ACE2 Recognition by the SARS-CoV-2 Spike Glycoprotein
62(4)
SARS-CoV-2 S Protein CTD Interactions with Human ACE2 Receptor
63(1)
Correlation of the SARS-CoV-2-RBD and SARS-CoV-RBD Interaction with Human ACE2 Receptor
63(1)
Exhibits Distinct Epitope Features of SARS-CoV-2 on the RBD from SARS-CoV
64(2)
Computation Approach
66(33)
Q-UEL Methods
66(1)
Theory Behind the General Strategy
66(1)
Fundamental Principles of Epitope Prediction for Design of Synthetic Immunizations
66(1)
Q-UEL: A Knowledge Representation Toolkit
67(1)
Sources Data and Material
67(1)
Important Notation
68(1)
Results
69(26)
Machine Learning Clustering Technique
95(1)
Genome Sequence Analysis
95(2)
K-Means Cluster Algorithm
97(2)
Dataset
99(1)
Results
99(2)
Notes
101(1)
References
101(10)
PART II COVID-19 Screening, Testing and Detection Systems: Different Paths to the Same Destination
Chapter 3 Real Time-Polymerase Chain Reaction (RT-PCR) and Antibody Test
111(54)
Introduction
111(1)
Real Time RT-PCR
112(9)
RT-PCR Method in Testing
113(1)
Principle Behind RT-PCR Testing
114(1)
How Does RT-PCR Work in Coronavirus Case?
115(1)
Nucleic Acid Testing
115(2)
Nucleic Acid Testing for SARS-CoV-2
117(1)
Integrating Nucleic Acid Detection with Clinical Management
118(1)
Device Description and Test Principle
118(1)
Description of Pooling
119(2)
Computational Technique of RT-PCR Test Diagnostic Sensitivity and Specificity Reconstruction for COVID-19
121(8)
Data and Methods
122(1)
Data
122(1)
Statistical Analysis
123(2)
Results
125(4)
Digital Polymerase Chain Reaction
129(15)
Statistical Foundations of dPCR
130(1)
Binomial Probability and Poisson Approximation
130(1)
Quantification Accuracy
131(1)
Most Probable Number (MPN)
131(1)
Copy Number Variant (CNV) Applications
132(1)
Absolute Limit of Quantification Due to Specimen Sampling
133(1)
Hypothesis and Technological Implications
133(1)
Conclusion of the Statistical Foundations of dPCR
134(1)
Performance Metrics
134(1)
Sensitivity of Detection
134(1)
Dynamic Range of Detection
135(1)
Practical Considerations in the Reliability of dPCR Measurements-False-Negative/Positive Signals
135(1)
Miniaturization and Hyper-Compartmentalization
136(1)
Chamber Formats
137(7)
Computational Technique of ddPCR Test for Sensitivity Assessment of COVID-19
144(4)
Materials and Methods
145(1)
Specimens Collection, Storage, and Pooling
145(1)
Preparation of Groups of 16 and 32 Individuals
146(1)
Detection of SARS-CoV-2 by Grouped, DPCR Testing
146(1)
Detection of SARS-CoV-2 by Routine Individual RT-PCR Testing
146(2)
Individual Confirmatory Testing for SARS-CoV-2 By RT-PCR and DPCR
148(1)
LoB/LoD Evaluation for SARS-CoV-2 Detection Using DPCR
148(1)
Results
148(10)
Cohort Description from Routine RT-PCR Testing
148(1)
Results from Grouped DPCR Testing
149(1)
Detailed Results for DPCR in Groups of 8
150(2)
Detailed Results for DPCR in Groups of 16
152(1)
Detailed Results for DPCR in Groups of 32
153(1)
Investigation of RT-PCR-/dPCR+ Discordances
153(1)
Investigation of the Sample RT-PCR+/dPCR
153(2)
Correlation between DPCR Measurements and Ct Values
155(3)
References
158(7)
Chapter 4 Antigen-Antibody Reaction-Based Immunodiagnostics Method
165(38)
Introduction
165(1)
Definition of Basic Terms of Immunoassays for Disease
166(5)
The Immune System
166(1)
Immunoassays
167(1)
Serology Testing
168(1)
Antigens
169(1)
Antibodies
169(1)
Antibody Functions
170(1)
Affinity, Avidity, and Cross Reactivity
170(1)
Emerged Rapid Immunodiagnostic (Serology Immunoassays) Tests
171(2)
Lateral Flow Immunoassay
171(1)
Immunoenzymatic and Immunofluorimetric Assays
172(1)
SARS-CoV-2 Infectivity and Immune Response
173(2)
Viral Infectivity
174(1)
Immune Response to COVID-19 Disease
174(1)
COVID-19 Antibody Response: Pathogenic or Protective?
175(1)
Computational Method
175(11)
Immunoinformatics-Based Analysis
175(1)
Data and Material
175(1)
Predicting Potential Linear B-Cell Epitopes in SARS-CoV-2
176(1)
Prediction of Potential T-Cell Epitopes in SARS-CoV-2
176(1)
Prediction of Protective Antigens
176(1)
Analysis of Epitope Conservation and Population Coverage of T-Cell Epitopes
177(1)
Prediction of Allergenicity, Toxicity, and Possibilities of Autoimmune Reactions
177(1)
Result
177(9)
Support Vector Machine to Predict B-Cell
186(11)
Data and Material
186(1)
Methodology
186(4)
Performance Evaluation
190(1)
Result
190(7)
References
197(6)
PART III COVID-19 Detection: Advanced Image Processing with Artificial Intelligence Techniques
Chapter 5 Lung Function Testing (LFT) with Normal CT Scans and AI Algorithm
203(38)
Introduction
203(1)
General Consideration of PFT for COVID-19
204(2)
Lung Structure
205(1)
Lung Function
206(1)
Review of Chest CT Findings in Early COVID-19 Studies
206(2)
Monitoring the Severity and Progression of COVID-19 with Chest CT
208(1)
Correlation of Testing with rRT-PCR and Chest CT
208(1)
The Ability to Differentiate Between COVID-19 Pneumonia and Other Pneumonias
209(1)
Deep Learning Architectures for CT SCAN
209(27)
Detection of COVID-19 Using UNet ConvNet
210(1)
UNeTConvNet
210(1)
Data and Material
211(1)
Methodology
212(1)
Results
213(1)
Advantages of UNet
214(1)
Ensemble of Convolutional Autoencoder and Random Forest
215(1)
Data and Material
215(1)
Methodology
215(2)
Result Analysis
217(4)
Fully Connected Segmentation Neural Network (FCSegNet)
221(1)
Data and Material
222(2)
Methodology
224(5)
Implementation Details
229(1)
Result
229(7)
Note
236(1)
References
236(5)
Chapter 6 Chest X-Ray Image-Based Testing Using Machine Learning Techniques
241(38)
Introduction
241(1)
Chest X-Ray Imaging for COVID-19
242(6)
Ground Glass Opacity of COVID-19 Pneumonia
242(2)
Usually Affected Part of Lungs with COVID-19
244(2)
Reliability of Detecting COVID-19 Using Chest X-Ray
246(1)
Features and Limitations of Chest Radiographs in COVID-19
247(1)
Features
247(1)
Limitations
248(1)
Machine Learning Architectures for Chest X-Ray
248(26)
Ensemble Feature Optimization with KNN Classification
248(1)
Image-Based Classification Method
249(2)
Feature Selection
251(3)
Data and Metrical
254(1)
Methodology
254(2)
Results and Discussion
256(1)
Deep Convolutional Neural Networks
257(3)
Data and Material
260(1)
Methodology
260(4)
Result
264(3)
ResNet50, InceptionV3, and InceptionResNetV2 Models
267(1)
Data and Material
267(1)
Deep Transfer Learning
268(1)
Experimental Setup
269(5)
References
274(5)
Chapter 7 Blood Cell Microscope Image-Based Testing Using Deep Learning Techniques
279(18)
Introduction
279(1)
COVID-19 and Blood Analysis: A Case Study
279(1)
Computation Techniques
280(13)
YOLO Model
280(1)
Data and Material
280(1)
Methodology
281(1)
Result
282(3)
Parasitemia Evaluation Methods
285(1)
Preprocessing
285(5)
Parasites Detection
290(2)
Results
292(1)
Notes
293(1)
References
293(4)
PART IV Analysis of the Pre- and Post-Impact of the COVID-19 Pandemic Crisis
Chapter 8 Direct and Indirect Impacts of Environmental Factors on the COVID-19 Pandemic
297(50)
Introduction
297(2)
COVID-19 and Other Large-Scale Epidemic Diseases of the 21st Century
299(3)
COVID-19 Environmental Impacts
302(18)
Impacts on the Physical Systems of the Environment
302(1)
Air Quality and Local Climate
303(7)
Impact on Water Resources
310(3)
Impact on Aquatic Systems and Wildlife
313(3)
Impacts on the Ecological Systems
316(1)
Impacts on Environmental Dimension of the Global Affairs
317(1)
Environmental Monitoring and Climate Services
318(2)
Impacts on the Present Climate and Climate Change
320(2)
Artificial Intelligence Tools and Techniques to Measure and Analysis the Impact of COVID-19 on Environment
322(17)
Time Series Analysis
322(1)
The Study Area
323(1)
Materials and Methods
323(4)
Results
327(12)
Summary
339(1)
Notes
340(1)
References
341(6)
Chapter 9 Direct and Indirect Impacts of the COVID-19 Pandemic Crisis on Economy
347(38)
Introduction
347(3)
Impact Analysis from Past Epidemics as a Statistical Lesson
350(2)
Pandemic Scenario
352(1)
Global Pandemic Scenario
352(1)
Amplified Global Pandemic Scenario
353(1)
Global Economy Affection and Policies to Competing COVID-19
353(2)
Governments Policy
353(1)
Non-Government Business Policy
354(1)
Direct and Indirect Costs
355(8)
Direct Cost
356(1)
Indirect Cost
356(1)
Supply Shocks
357(2)
Demand Shocks and Fluctuation
359(4)
Computational Model for Visual Analysis of COVID-19's Impact on the Global Economy
363(9)
Envisage Model
363(1)
World Supply Shock Capacity Reduction
364(3)
Trade Costs
367(1)
International Tourism
368(1)
Consumer Confidence and Demand Fluctuation
368(4)
COVID-19 and the Stock Market Uncertainty Analysis Using Time Series Model
372(8)
Method and Material
374(1)
Model Description
375(1)
Results and Discussion
376(3)
Coronavirus and Unemployment Rates
379(1)
Summary
380(1)
Notes
381(4)
Chapter 10 Direct and Indirect Impacts of the COVID-19 Pandemic Crisis on Food & Agriculture
385(42)
Introduction
385(1)
The Impact of COVID-19 on Agriculture-Food Market
386(4)
Food Supply
388(2)
Food Demand
390(1)
Immediate Impacts
390(4)
Food Security
391(1)
Labour Availability
392(1)
Farm System Resilience
393(1)
Agricultural System Connectivity
393(1)
Other Impacts and Questions
394(1)
Computation Model of Analysis
394(18)
Dynamic Panel Model
394(1)
Impact of Pandemic on Food Safety Level
395(1)
Data Description
396(2)
Results and Discussions
398(4)
Spatial Durbin Model
402(1)
Production Function and Growth Accounting Model
403(1)
Data and Summary Statistics
404(1)
Results and Discussion
405(7)
Time Series Analysis
412(9)
Economic Impact on Agriculture: World
412(5)
Economic Impact on Agriculture: India
417(4)
Summary
421(1)
Notes
422(1)
References
422(5)
Chapter 11 Direct and Indirect Impacts of the COVID-19 Pandemic Crisis on Hotels, Tour and Travel Sectors
427(38)
Introduction
427(1)
Current Situation in the Tourism Sector
428(1)
COVID-19 Circumstances and Tourism
429(5)
COVID-19: Dismantling and Re-Mantling Tourism in Three Stages
434(8)
Tourism Demand
439(1)
Tourism Supply--Businesses
440(1)
Destination Management Organizations and Policymakers
441(1)
Impact of the Current Crisis on Tourism Destinations
442(5)
Chile Tourism
442(1)
Mexico Tourism
442(1)
Spain Tourism
442(2)
China Tourism
444(1)
The United Kingdom Tourism
445(1)
Turkey Tourism
445(1)
Thailand Tourism
446(1)
Global Impact
446(1)
Computational Models for Tourism Demand Forecasting
447(13)
LSTM Model
447(1)
Methodology & Data
447(8)
Support Vector Regression (SVR)
455(2)
Shock
457(1)
Fear
457(1)
Result and Discussion
458(2)
Expected Impactful Sectors Analysis
460(2)
Airlines Sector
460(1)
Cruise Industry
461(1)
Fair Industry
461(1)
Tourist Apartment
461(1)
Business Travel
461(1)
Nightly Leisure
462(1)
Fashion and Luxury (Shopping Tourism)
462(1)
Notes
462(1)
References
462(3)
Chapter 12 Direct and Indirect Impacts of the COVID-19 Pandemic Crisis on Human Physical and Physiological Health
465(42)
Introduction
465(1)
Impact of COVID-19 and Physical Inactivity on The Immune System
466(6)
COVID-19, Physical Activity, and the Respiratory System
468(1)
Impact of COVID-19 and Physical Inactivity on Cardiovascular System
469(1)
Impact of COVID-19 and Physical Inactivity on Musculoskeletal System
470(2)
COVID-19 Infection and the Brain Function
472(1)
Does SARS-Cov-2 Infection Threaten and Damage the Brain?
472(1)
Can Physical Fitness Protect or Attenuate the Consequences of Infection?
472(1)
Recommendation to Fight Against COVID-19-Associated Neurological and Mental Disorders
473(1)
Impact of COVID-19 on Older Adults
474(2)
Possible Effects of COVID-19 on Muscle Atrophy and Physical Function
474(1)
Are Frailty and Sarcopenia Possible Outcomes of COVID-19?
475(1)
Computational Approach to Analysis Impact of COVID-19 on Human Physiological Health
476(22)
Literature Review
478(2)
Textual Analytics
480(1)
Twitter Analytics
480(2)
Classification Methods
482(2)
Methods and Textual Data Analytics
484(1)
Exploratory Textual Analytics
485(1)
Data Acquisition and Preparation
486(1)
Word and Phrase Associations
486(1)
Geo-Tagged Analytics
487(1)
Association with Non-Textual Variables
487(2)
Sentiment Analytics
489(1)
Machine Learning with Classification Methods
489(1)
Naive Bayes Classifier
490(2)
Logistic Regression
492(3)
A Digital Mental Health Revolution
495(1)
Telehealth
495(1)
Mental Health Smartphone Applications
496(1)
Texting Applications
497(1)
Social Media
497(1)
Notes
498(1)
References
498(9)
Index 507
Mr. Parag Verma Mr. Parag Verma is working as Assistant Professor at Uttaranchal University, Dehradun. He is having a long experience of 8+ years in the field of industry and academics. He is having 15+ international papers in reputed conferences and journals. He has contributed 2 books with publishers like Nerosa and Alpha, and currently working on 2 more accepted books. He had also contributed 4 chapters for reputed publishers. He is also an editorial board member of many reputed conferences and journals including Scopus. He is also a guest editor of IJNCDS (Scopus Indexed inderscience Journal) and many more. He is associated with many societies and organizations for the welfare of educationalist societies.

Dr. Ankur Dumka is working as Associate Professor in Graphic Era Deemed to be University, Dehradun. He is having a long experience of 10+ years in the field of industry and academics. He is associated with smart city Dehradun as an academic expert committee member and co-ordinator in terms of projects related to IT. He is having 40 + international papers in reputed conferences and journals. He has contributed 3 books with publishers like Taylor and Francis, IGI global, etc. and currently working on 3 more accepted books. He had also contributed 14 chapters for reputed publishers. He is also editorial board members of many reputed conferences and journals including Scopus and IEEE. He is also a guest editor of IJNCDS (Scopus Indexed inderscience Journal), guest editor for IJNCR (ACM digital library -IGI global journal) and many more. He is associated with many societies and organizations for the welfare of educationalist societies.

Dr. Alaknanda ashok is working as dean and professor, college of technology, G.B.Pant university of Agriculture and technology, pantnagar. She is having a large administrative experience as director, women Institute of technology and controller of examiner of uttarakhand technical university. She is having more than 50 research papers in reputed journals and conferences of repute. She is having 3 patent published. She is having many research projects working under her supervision as project in charge. She is also having many book chapters and currently working on proposed books with Taylor and Francis. She is also associated with many journals and conferences in the capacity of editor, editorial board member and convener.

Amit Dumka is working as Deputy Manager in Government Medical College, Haldwani, India. He is having more than 17 years of experience with administrative and industry exposure. He is having many research papers in reputed journals and conferences. He is also associated with journals in the capacity of editorial board members and guest editor.

Dr. Anuj Bhardwaj, M. Tech. & Ph. D degree in computer science. He is currently a Professor of Computer Science & Engineering with Chandigarh University, Mohali, Punjab. He is having a long experience of 12+ years in the field of industry and academics. He is having 27+ international papers in reputed conferences and journals. He has contributed 2 books with publishers like Nerosa and Alpha, and currently working on 2 more accepted books. He had also contributed 6 chapters for reputed publishers. His current research interests include pattern & character recognition, graphics & vision, artificial intelligence & neural networks and machine learning.