The book *Mathematical Models in Population Biology and Epidemiology* by Fred Brauer and Carlos Castillo-Chavez is a comprehensive resource that aims to bridge the gap between mathematics and biology. The second edition, revised and updated, covers a wide range of topics in population dynamics and epidemiology, reflecting the significant advancements in the field over the past decade. The authors have maintained the core content of the first edition while incorporating new chapters and expanded sections on spatiotemporal dynamics, disease dynamics, and control. Key features of the book include: - **Core Content**: The book covers fundamental models in population biology, such as exponential growth, the logistic model, and discrete-time models, providing a solid foundation for understanding population dynamics. - **Advanced Topics**: It delves into more complex models, including models with delays, age structure, and spatial structure, which are crucial for understanding structured populations. - **Epidemiology**: The book includes detailed chapters on epidemic models, disease transmission, and endemic diseases, with a focus on parameter estimation and real-world applications. - **Practical Applications**: Each chapter includes exercises and projects that encourage readers to apply mathematical concepts to real-world scenarios, enhancing their understanding and problem-solving skills. - **Supplementary Materials**: Additional exercises, detailed solutions, and supplementary materials are available online, making the book a valuable resource for both students and researchers. The book is designed to be accessible to students in the biological sciences and mathematics, with a focus on qualitative methods and approximate solutions rather than detailed proofs. It emphasizes the importance of computer algebra systems and software like Maple, Matlab, and Mathematica for visualizing and analyzing models. The authors also acknowledge the contributions of numerous individuals and institutions, highlighting the collaborative nature of the field and the ongoing efforts to advance mathematical modeling in biology.The book *Mathematical Models in Population Biology and Epidemiology* by Fred Brauer and Carlos Castillo-Chavez is a comprehensive resource that aims to bridge the gap between mathematics and biology. The second edition, revised and updated, covers a wide range of topics in population dynamics and epidemiology, reflecting the significant advancements in the field over the past decade. The authors have maintained the core content of the first edition while incorporating new chapters and expanded sections on spatiotemporal dynamics, disease dynamics, and control. Key features of the book include: - **Core Content**: The book covers fundamental models in population biology, such as exponential growth, the logistic model, and discrete-time models, providing a solid foundation for understanding population dynamics. - **Advanced Topics**: It delves into more complex models, including models with delays, age structure, and spatial structure, which are crucial for understanding structured populations. - **Epidemiology**: The book includes detailed chapters on epidemic models, disease transmission, and endemic diseases, with a focus on parameter estimation and real-world applications. - **Practical Applications**: Each chapter includes exercises and projects that encourage readers to apply mathematical concepts to real-world scenarios, enhancing their understanding and problem-solving skills. - **Supplementary Materials**: Additional exercises, detailed solutions, and supplementary materials are available online, making the book a valuable resource for both students and researchers. The book is designed to be accessible to students in the biological sciences and mathematics, with a focus on qualitative methods and approximate solutions rather than detailed proofs. It emphasizes the importance of computer algebra systems and software like Maple, Matlab, and Mathematica for visualizing and analyzing models. The authors also acknowledge the contributions of numerous individuals and institutions, highlighting the collaborative nature of the field and the ongoing efforts to advance mathematical modeling in biology.