COVID-19 : origin, detection and impact analysis using artificial intelligence computational techniques / Parag Verma [and four others].

Format:

Book

Author/Creator:

Verma, Parag, author.

Language:

English

Subjects (All):

COVID-19 (Disease)--Data processing.

COVID-19 (Disease).

Physical Description:

1 online resource (529 pages)

Edition:

1st ed.

Place of Publication:

Boca Raton, Florida : CRC Press, [2021]

Summary:

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.

Contents:

Cover

Half Title

Title Page

Copyright Page

Dedication

Contents

Authors

PART I: Origin and Background of COVID-19

Chapter 1: Introduction to Emerging Respiratory Viruses with Coronavirus Disease (COVID-19)

Introduction

New and Newly Recognized Respiratory Viruses

Influenza Viruses

H1N1 Influenza

H2N2 Influenza

Avian Influenza (AI)

A(H7N9) Virus

A(H5N1) Virus

Other AI Viruses

Hantavirus

Human Metapneumovirus (HMPV)

Bocavirus

Coronavirus

HCoV-229E and HCoV-OC43

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)

Middle East Respiratory Syndrome Coronavirus (MERS-CoV)

SARS-CoV-2

Timeline of the Emerging Viruses

Current Worldwide Scenario of SARS-CoV-2

Time Line of the Outbreak

Emergence of Coronavirus (SARS-CoV-2)

Compression of Coronaviruses in Humans-SARS-CoV, MERS-CoV, and COVID-19

Prevention, Control, and Management Strategies from SARS-CoV-2

Containment Strategies for SARS-CoV-2: Isolation, Quarantine

Principles of Modern Quarantine

Computational Technique of Analysis Effect of Containment Strategies

SIR Model for Pandemics

SIQR Model

SEIR Model

SEIRS Model

Additional Preventions Tips for Community

Case and Contact Management

Community Containment

Notes

References

Chapter 2: The Origin Molecular Structure, Function, and Evolution Insights of COVID-19: Morphogenesis and Spike Proteins

Emergence of SARS-CoV and SARS-CoV-2

Classification of Coronaviruses

Key Features and Entry Mechanism of Human Coronaviruses

Morphology, Genomic Structure, and Its Variation of SARS-CoV-2

Genome Sequencing

Genome Structure

Accessory Proteins

Structural Proteins of Viral

S Protein

E Protein

M Protein

N Protein.

Structure, Function, Antigenicity, and ACE2 Recognitionby the SARS- CoV-2 Spike Glycoprotein

SARS-CoV-2 S Protein CTD Interactions with HumanACE2 Receptor

Correlation of the SARS-CoV-2-RBD and SARS-CoV-RBD Interaction with Human ACE2 Receptor

Exhibits Distinct Epitope Features of SARS-CoV-2 onthe RBD from SARS-CoV

Computation Approach

Q-UEL Methods

Theory Behind the General Strategy

Fundamental Principles of Epitope Prediction for Design of Synthetic Immunizations

Q-UEL: A Knowledge Representation Toolkit

Sources Data and Material

Important Notation

Results

Machine Learning Clustering Technique

Genome Sequence Analysis

K-Means Cluster Algorithm

Dataset

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

Real Time RT-PCR

RT-PCR Method in Testing

Principle Behind RT-PCR Testing

How Does RT-PCR Work in Coronavirus Case?

Nucleic Acid Testing

Nucleic Acid Testing for SARS-CoV-2

Integrating Nucleic Acid Detection with Clinical Management

Device Description and Test Principle

Description of Pooling

Computational Technique of RT-PCR Test Diagnostic Sensitivity and Specificity Reconstruction for COVID-19

Data and Methods

Data

Statistical Analysis

Digital Polymerase Chain Reaction

Statistical Foundations of dPCR

Binomial Probability and Poisson Approximation

Quantification Accuracy

Most Probable Number (MPN)

Copy Number Variant (CNV) Applications

Absolute Limit of Quantification Due to Specimen Sampling

Hypothesis and Technological Implications

Conclusion of the Statistical Foundations of dPCR

Performance Metrics

Sensitivity of Detection.

Dynamic Range of Detection

Practical Considerations in the Reliability of dPCR Measurements-False -Negative/Positive Signals

Miniaturization and Hyper Compartmentalization

Chamber Formats

Computational Technique of ddPCR Test for Sensitivity Assessment of COVID-19

Materials and Methods

Specimens Collection, Storage, and Pooling

Preparation of Groups of 16 and 32 Individuals

Detection of SARS-CoV-2 by Grouped DPCR Testing

Detection of SARS-CoV-2 by Routine Individual RT-PCR Testing

Individual Confirmatory Testing for SARS-CoV-2 By RT-PCR and DPCR

LoB/LoD Evaluation for SARS-CoV-2 Detection Using DPCR

Cohort Description from Routine RT-PCR Testing

Results from Grouped DPCR Testing

Detailed Results for DPCR in Groups of 8

Detailed Results for DPCR in Groups of 16

Detailed Results for DPCR in Groups of 32

Investigation of RT-PCR-/dPCR+ Discordances

Investigation of the Sample RT-PCR+/dPCR

Correlation between DPCR Measurements and Ct Values

Chapter 4: Antigen-Antibody Reaction-Based Immunodiagnostics Method

Definition of Basic Terms of Immunoassays for Disease

The Immune System

Immunoassays

Serology Testing

Antigens

Antibodies

Antibody Functions

Affinity, Avidity, and Cross Reactivity

Emerged Rapid Immunodiagnostic (Serology Immunoassays) Tests

Lateral Flow Immunoassay

Immunoenzymatic and Immunofluorimetric Assays

SARS-CoV-2 Infectivity and Immune Response

Viral Infectivity

Immune Response to COVID-19 Disease

COVID-19 Antibody Response: Pathogenic or Protective?

Computational Method

Immunoinformatics-Based Analysis

Data and Material

Predicting Potential Linear B-Cell Epitopes in SARS-CoV-2

Prediction of Potential T-Cell Epitopes in SARS-CoV-2

Prediction of Protective Antigens.

Analysis of Epitope Conservation and Population Coverage of T-Cell Epitopes

Prediction of Allergenicity, Toxicity, and Possibilities of Autoimmune Reactions

Result

Support Vector Machine to Predict B-Cell

Methodology

Performance Evaluation

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

General Consideration of PFT for COVID-19

Lung Structure

Lung Function

Review of Chest CT Findings in Early COVID-19 Studies

Monitoring the Severity and Progression of COVID-19 with Chest CT

Correlation of Testing with rRT-PCR and Chest CT

The Ability to Differentiate Between COVID-19 Pneumonia and Other Pneumonias

Deep Learning Architectures for CT SCAN

Detection of COVID-19 Using UNet ConvNet

UNeT ConvNet

Advantages of UNet

Ensemble of Convolutional Autoencoder and Random Forest

Result Analysis

Fully Connected Segmentation Neural Network (FCSegNet)

Implementation Details

Note

Chapter 6: Chest X-Ray Image-Based Testing Using Machine Learning Techniques

Chest X-Ray Imaging for COVID-19

Ground Glass Opacity of COVID-19 Pneumonia

Usually Affected Part of Lungs with COVID-19

Reliability of Detecting COVID-19 Using Chest X-Ray

Features and Limitations of Chest Radiographs in COVID-19

Features

Limitations

Machine Learning Architectures for Chest X-Ray

Ensemble Feature Optimization with KNN Classification

Image-Based Classification Method

Feature Selection

Data and Metrical

Results and Discussion.

Deep Convolutional Neural Networks

ResNet50, InceptionV3, and InceptionResNetV2 Models

Deep Transfer Learning

Experimental Setup

Chapter 7: Blood Cell Microscope Image-Based Testing Using Deep Learning Techniques

COVID-19 and Blood Analysis: A Case Study

Computation Techniques

YOLO Model

Parasitemia Evaluation Methods

Preprocessing

Parasites Detection

PART IV: A 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

COVID-19 and Other Large-Scale Epidemic Diseases of the 21st Century

COVID-19 Environmental Impacts

Impacts on the Physical Systems of the Environment

Air Quality and Local Climate

Impact on Water Resources

Impact on Aquatic Systems and Wildlife

Impacts on the Ecological Systems

Impacts on Environmental Dimension of the Global Affairs

Environmental Monitoring and Climate Services

Impacts on the Present Climate and Climate Change

Artificial Intelligence Tools and Techniques to Measureand Analysis the Impact of COVID-19 on Environment

Time Series Analysis

The Study Area

Summary

Chapter 9: Direct and Indirect Impacts of the COVID-19 Pandemic Crisis on Economy

Impact Analysis from Past Epidemics as a Statistical Lesson

Pandemic Scenario

Global Pandemic Scenario

Amplified Global Pandemic Scenario

Global Economy Affection and Policies to Competing COVID-19

Governments Policy

Non-Government Business Policy

Direct and Indirect Costs

Direct Cost

Indirect Cost.

Supply Shocks.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

1-00-313141-7

1-003-13141-7

1-000-39170-1

9781003131410

OCLC:

1259320375