This compendium represents a set of guides to understanding the challenging scientific, epidemiological, clinical, social, and economic phenomenon that is represented by the COVID-19 pandemic.
The book explains the mathematical modeling of COVID-19 infection, with emphasis on traditional epidemiological principles. It represents a rigorous, comprehensive and multidisciplinary approach to a complex phenomenon. The chapters take into account the knowledge arising from different disciplines (epidemiology, pathophysiology, immunology, medicine, biology, vaccine development, etc.). It also covers COVID-19 data analysis, giving the reader a perspective of statistics and data science, and includes a discussion about social and economic issues of the pandemic. Each chapter is devoted to a specific topic, and is contributed by experts in epidemiology.
Because of its multidisciplinary nature, this book is intended as a reference on mathematical models and basic immunotherapy for COVID-19 for a broad community of readers, from scholars who have scientific training, to general readers who have an interest in the disease.
Author(s): Andrés Fraguela-Collar
Publisher: Bentham Science Publishers
Year: 2022
Language: English
Pages: 582
City: Singapore
Cover
Title
Copyright
End User License Agreement
Contents
Foreword I
Foreword II
Foreword III
Preface
List of contributors
An Approach to COVID-19: Current Results, Perspectives and its Study with Mathematical and Computational Modeling Tools
Introduction
Importance
The COVID-19 Pandemic as a Complex Phenomenon
Mathematical and Computational Modeling in Epidemiology
Different Perspectives for the Study of the Disease and the COVID-19 Pandemic
Action of the Virus at Different Scales of Biological Organization
Temporal Evolution of COVID-19 Disease at the Individual Level
Temporal Evolution of the COVID-19 Pandemic at the Country Level and at the Global Level; the Role of Human Mobility
Collateral Consequences for Human Health, Society and the Economy; Final Comments
Mathematical and Computational Modeling of COVID-19: Results and Perspectives
Main Characteristics of Forecasting and Compartmental Models and the Basic Assumptions that Support Them
Renewal Equations: Another Scheme for the Construction of Compartmental Models
Methodology for the Application of Compartmental Models of the SIR-Type
What Are Compartmental Epidemiological Models Useful for and What Are Their Limitations?
How Are the Components of an Epidemiological Compartmental Model Constructed in Correspondence with the Application It Is Intended for?
Some Important Results Obtained on COVID-19 with the Use of Compartmental Mathematical Models
Some Pending Issues in the Collection and Analysis of Data and in the Study of the Mathematical Models, Associated with COVID-19
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Epidemiology of COVID-19
Introduction
Importance
Preliminaries
Coronaviruses of Public Health Importance
The SARS-CoV-2 Virus
Origin and Evolution of the Pandemic
International Health Regulations and Mechanisms for Preparing and Responding to Threats to Public Health
What Is a Public Health Emergency of International Concern?
Global Epidemiological Situation and in Mexico of COVID-19
Transmission Mechanisms and ``Reproduction Number'' (R0)
Preventive Measures
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
COVID-19 Pathophysiology, Clinical Manifestations, and Drug Treatment
Introduction
Importance
Preliminaries
Pathophysiology of the Disease
Virology
Inflammatory Response
Thrombotic Phenomena
Clinical Manifestations of SARS-CoV-2 Infection
Asymptomatic Infection
Symptomatic Infection
Clinical Manifestations
Drug Treatment
Convalescent Patient Plasma
Remdesivir
Baricitinib
Anticoagulation and COVID-19
Steroid Use in COVID-19
Tocilizumab
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Modelling Epidemics: a Perspective on Mathematical Models and Their Use
Introduction
Importance
Preliminaries
Basic Results of the Kermack-McKendrick Model
More General Models
Modification of the Basic Models
Epidemic Curves
Epidemic Interactions
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Data Science: A Useful Tool for Understanding SARS-CoV-2 Information Facts
Introduction
Importance
Preliminaries
Artificial Intelligence: the New Boom
General Framework of Data Science Projects
The Data Science Workflow
Exploratory Data Analysis and Preprocessing
Case Study: the Mexican COVID-19 Data
The Database
Bayesian Networks
Decision Trees
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Epidemic Progression in a Heterogeneously Distributed Population
Introduction
Importance
Epidemiological Situation
Epidemiological Modelling
Model Problem for a Heterogeneous Population
Basic Reproduction Number
Final Size of the Epidemic
Maximum Number of Infected Individuals
Model with Reinfection
Basic Reproduction Number
Existence of Endemic Equilibrium
Final Size of the Epidemic
Multipatch Model
Two-Group Single-Patch Model
Two-Group n Patch Model
Epidemic Progression in Some States in India
Epidemic Progression in Maharashtra
Epidemic Progression in the Neighboring States
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Social Inequalities in COVID-19
Introduction
Importance
Preamble
Preliminaries
Context and Health in the Life Course
The Right to Health
Conceptual Bases for Measuring Social Inequalities Related to Health
Common Contexts and Applications of Inequality Measurement
Basic Properties and Desirable Attributes for Health Inequality Indices
A Basic Taxonomy of Indices to Measure Inequalities bib07053
Indices for Ordered Categories
Indices Based on Pairwise Comparisons
Indices Based on the Regression Model
The Concentration Index (CI)
Indices for Non-Ordered Categories
Indices Based on Pairwise Comparisons
Dispersion Indices
Indices Based on the Comparison of Two Probability Distributions
Options in Measuring Social Inequalities in Relation to Health
COVID-19 and Inequalities. Some Selected Results
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Statistical Approaches to Understand COVID-19 Severity and Fatality
Introduction
Importance
Preliminaries
Basic Statistics Applied to COVID-19 Severity
Confirmed Cases, Severity, and Recovery or Death
Burden of COVID-19
Cluster Analysis for Patient Stratification
Prediction Models for Severity and Fatality
Case-Example: Predictors of COVID-19 Fatality in Cuba
Background
Materials and Methods
Results and Discussion
Further Applications of Statistical and Epidemiological Techniques
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Understanding the Impact of Cuban Immunotherapy Protocols During COVID-19 Disease: Contributions from Mathematical Modeling and Statistical Approaches
Introduction
Importance
Preliminaries
Mathematical Model Presentation
Model Assumptions
Model Equations
Model Results
Itolizumab on COVID-19
Preliminary Evidences from the Clinical Practice
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Vaccines Against SARS-CoV-2. Eradicating COVID-19
Introduction
Importance
Preliminaries
Vaccine Development Process
Fast-Track Procedures for COVID-19 Vaccine
Major COVID-19 Vaccine Approaches
Original Virus as Vaccine Platform
Other Viruses as Vaccine Platform
Genetic Material as Vaccine Platform
Protein/Peptides Delivered as Subunit Vaccines
Concluding Remarks
Consent for Publication
Conflict of Interest
Acknowledgements
References
Appendix: COVID-19 in charts
Subject Index
Back Cover
