Main description:

COVID Transmission Modeling: An Insight into Infectious Diseases Mechanism provides an interdisciplinary overview of the COVID-19 pandemic crisis and covers various aspects of newer modeling techniques and practical solutions for health emergencies. This book aims to formulate various innovative and pragmatic mathematical, statistical, and epidemiological models using COVID-19 real data sets. It emphasizes interdisciplinary theoretical postulates derived from practical insights and knowledge of public health. Each of the book's 12 chapters provides invaluable and exploratory tools to enable explicit assumptions, highlights key health indicators, and determines the geometric progression and control measures of the disease. The present developed models will allow readers to extrapolate the exact reason for the outbreak and pave the way for scientific information on vaccine trials and socioeconomic, psychological, and disease burden worldwide. These advanced techniques of modeling and their applications are in greater need than ever for effective connection between mathematicians, statisticians, epidemiologists, researchers, clinicians, and policymakers for making appropriate decisions at the right time. With the advent of emerging health science, all models are demonstrated with real-life data sets and provided with illustrations and eye-catching graphs and diagrams so that the readers can easily understand the concept of COVID-19 pandemic interventions and their control measures, and their impact.

Features

Addresses all aspects of mitigation/control measures, estimation of transmission rate, economic impact assessment, genetic complexity of COVID-19, herd immunity, and various methods, including newer mathematical, statistical, and epidemiological models in the analysis of COVID-19 pandemic outbreak
Covers the application of innovative, advanced statistical and epidemiological models and demonstrates possible solutions toward supportive treatment aspects of COVID-19 and its control measures
Includes models that can easily be followed in formulating the mathematical derivations and key points
Supplemented with ample illustrations, images, diagrams, and figures

This book is aimed at postgraduate students studying medicine and healthcare, mathematics, and statistical information. Researchers will also find this book very helpful.

Contents:

1. Mathematical Modeling Approach to COVID-19: Vetted Real Data.

2. Time Series Stochastic Projection Models for the Estimation of COVID Trend

3. Study of Anxiety and Fear of COVID-19

4. COVID-19 Gene Sequencing Modeling

5. Real-Time PCR (RT-PCR) for COVID-19 Diagnosis and Changes in Threshold Cycle (Ct) in Association with Different Parameters

6. COVID-19 Vaccination Modeling Approach to Public Health Policy

7. Trend of COVID-19 Surge Projection

8. Risk Analysis of COVID-19-Vetted by Real Data Sets

9. Data-Driven Decision Support Model for COVID-19

10. Age-Specific SARS-Cov-19 Incidence Modeling

11. National Health Policies and Their Perspectives on the Approach to Control COVID-19 and Other Infectious Diseases

12. Statistical Ethics for Computational Biology and Medical Science