Fractional Stochastic Differential Equations: Applications to Covid-19 Modeling by Abdon Atangana (Author), Seda İgret Araz (Author)

This book explores the application of fractional stochastic differential equations in modeling the dynamics of complex systems, with a special focus on the Covid-19 pandemic. Authored by Abdon Atangana and Seda İgret Araz, it delves into the mathematical techniques and tools needed to understand and predict stochastic processes in epidemiology.

Key Points:

1. Introduction to Fractional Calculus: Provides a comprehensive overview of fractional calculus and its use in differential equations, establishing a foundation for complex modeling.

2. Stochastic Processes in Epidemiology: Focuses on the role of stochastic processes in understanding the unpredictable nature of disease spread, especially in the context of Covid-19.

3. Covid-19 Modeling Applications: Illustrates how fractional stochastic differential equations can be used to model the spread and impact of Covid-19, providing insights into real-world applications.

4. Mathematical Framework: Offers a detailed mathematical framework for constructing and solving fractional stochastic differential equations.

5. Practical Examples and Case Studies: Includes real-world examples and case studies demonstrating the application of these equations in the context of Covid-19.

6. Interdisciplinary Approach: Combines concepts from mathematics, statistics, and epidemiology to create a holistic approach to disease modeling.

7. Tools and Techniques: Discusses various tools and techniques for solving fractional stochastic differential equations, aiding in the understanding and practical application of these methods.

8. Implications for Public Health: Examines the broader implications of this modeling approach for public health policy and decision-making during pandemics.

9. Advanced Research and Methodology: Addresses advanced research topics, offering insights for researchers and academics interested in fractional calculus and stochastic processes.

10. Practical Applications: Highlights the importance of these mathematical tools for predicting and managing the spread of infectious diseases, with a focus on how they can inform public health strategies.