Computational Epidemiology: Data-Driven Modeling of COVID-19

This textbook combines modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand the outbreak dynamics and outbreak control of COVID-19. It is for students, educators, basic scientists, medical researchers, and anyone passionate about big data and human health. It serves as a textbook for undergraduates and graduate students and a monograph for researchers and scientists.

Format: Hardback
Length: 312 pages
Publication date: 23 September 2021
Publisher: Springer Nature Switzerland AG

This groundbreaking textbook seamlessly integrates cutting-edge concepts from mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to delve into one of the most pressing challenges of our contemporary era: the intricate dynamics and effective control of the COVID-19 pandemic. By imparting the necessary tools to model and simulate nonlinear dynamic systems in the context of a global pandemic that profoundly impacts human health, it equips students, educators, basic scientists, medical researchers, and enthusiasts alike with the knowledge and expertise to navigate this critical domain. Whether you are a student, educator, aspiring researcher, or passionate advocate for big data and human health, this book is a invaluable resource. Serving as a comprehensive textbook for undergraduates and graduate students, as well as a monograph for researchers and scientists, it caters to a wide range of disciplines within the mathematical life sciences. Its applications extend to courses such as applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming. This book is a deeply personal reflection on the pivotal role of data-driven modeling during the COVID-19 pandemic, fueled by a relentless curiosity to unravel its complexities.

Key Features:

• Comprehensive Coverage: This textbook provides a comprehensive overview of the latest developments in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning, all of which are crucial in understanding the outbreak dynamics and outbreak control of COVID-19.


• Interdisciplinary Approach: The book adopts an interdisciplinary approach, drawing from various fields to provide a holistic understanding of the pandemic. It bridges the gap between mathematics, computer science, and health sciences, enabling students to apply their knowledge in a multidisciplinary context.


• Real-World Applications: The book showcases real-world case studies and examples from the COVID-19 pandemic, providing practical insights and applications of the theoretical concepts discussed.


• Hands-On Learning: The book includes hands-on exercises and code snippets, allowing students to apply the theoretical knowledge gained to real-world scenarios and gain practical experience in modeling and simulation.


• Accessible Writing: The writing style is accessible and engaging, making the textbook suitable for students with various backgrounds and learning styles.


• Future-Oriented: The book incorporates discussions on emerging technologies and future research directions, preparing students for the evolving challenges of the COVID-19 pandemic and beyond.

Who This Book Is For:

• Undergraduate Students: This textbook is an excellent resource for undergraduate students studying mathematics, computer science, health sciences, or related fields. It provides a foundational understanding of the key concepts and tools required to address the challenges of the COVID-19 pandemic.


• Graduate Students: Graduate students in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming will find this book invaluable. It offers in-depth coverage of the latest research and developments in the field.


• Basic Scientists: Basic scientists interested in understanding the mathematical aspects of the COVID-19 pandemic will find this book a valuable resource. It provides a comprehensive introduction to the relevant topics and enables them to contribute to interdisciplinary research efforts.


• Medical Researchers: Medical researchers seeking to enhance their understanding of the mathematical modeling and simulation of COVID-19 will find this book a must-read. It offers practical insights and techniques for developing effective models and analyzing data.


• Enthusiasts: Anyone with a passion for big data and human health will find this book intriguing. It provides a deep dive into the mathematical and computational tools used to combat the COVID-19 pandemic, offering a glimpse into the exciting field of data science.

Why This Book Is Important:

• Understanding the Complexity of the COVID-19 Pandemic: The COVID-19 pandemic has posed unprecedented challenges to global health, requiring a comprehensive understanding of the outbreak dynamics and effective control strategies. This textbook provides the necessary tools and knowledge to navigate this complex landscape.


• Data-Driven Approach: The book emphasizes the importance of data-driven modeling in understanding and addressing the challenges of the COVID-19 pandemic. It teaches students how to collect, analyze, and interpret data to develop accurate models and make informed decisions.


• Interdisciplinary Collaboration: The book fosters interdisciplinary collaboration by bringing together experts from various fields, enabling students to learn from and contribute to a diverse range of perspectives.


• Practical Applications: The book showcases real-world case studies and examples from the COVID-19 pandemic, providing practical insights and applications of the theoretical concepts discussed.


• Future-Oriented: The book incorporates discussions on emerging technologies and future research directions, preparing students for the evolving challenges of the COVID-19 pandemic and beyond.

Conclusion:

• In conclusion, this groundbreaking textbook is a must-read for anyone interested in understanding the outbreak dynamics and outbreak control of COVID-19. It seamlessly integrates cutting-edge concepts from multiple fields, providing students, educators, researchers, and enthusiasts with the knowledge and tools to navigate this critical domain. By leveraging data-driven modeling and interdisciplinary collaboration, we can collectively work towards mitigating the impact of the COVID-19 pandemic and building a more resilient and sustainable future.

Weight: 658g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030828899
Edition number: 1st ed. 2021