Superb, self-contained graduate-level text covers standard theorems concerning linear systems, existence and uniqueness of solutions, and dependence on parameters. Major focus on stability theory and its applications to oscillation phenomena, self-excited oscillations and regulator problem of Lurie. Bibliography. Exercises.

As the world population exceeds the six billion mark, questions of population explosion, or how many people the earth can support, and under which conditions, become pressing. The goal of this book is to search for a balance between simple and analyzable models and unsolvable models which are capable of addressing questions such as these. This book, which will include both examples and exercises, will be useful to practitioners, graduate students, and scientists working in the field.

Based on lecture notes of two summer schools with a mixed audience from mathematical sciences, epidemiology and public health, this volume offers a comprehensive introduction to basic ideas and techniques in modeling infectious diseases, for the comparison of strategies to plan for an anticipated epidemic or pandemic, and to deal with a disease outbreak in real time. It covers detailed case studies for diseases including pandemic influenza, West Nile virus, and childhood diseases. Models for other diseases including Severe Acute Respiratory Syndrome, fox rabies, and sexually transmitted infections are included as applications. Its chapters are coherent and complementary independent units. In order to accustom students to look at the current literature and to experience different perspectives, no attempt has been made to achieve united writing style or unified notation.

Notes on some mathematical background (calculus, matrix algebra, differential equations, and probability) have been prepared and may be downloaded at the web site of the Centre for Disease Modeling (www.cdm.yorku.ca).

Dynamical Systems for Biological Modeling: An Introduction prepares both biology and mathematics students with the understanding and techniques necessary to undertake basic modeling of biological systems. It achieves this through the development and analysis of dynamical systems.

The approach emphasizes qualitative ideas rather than explicit computations. Some technical details are necessary, but a qualitative approach emphasizing ideas is essential for understanding. The modeling approach helps students focus on essentials rather than extensive mathematical details, which is helpful for students whose primary interests are in sciences other than mathematics need or want.

The book discusses a variety of biological modeling topics, including population biology, epidemiology, immunology, intraspecies competition, harvesting, predator-prey systems, structured populations, and more.

The authors also include examples of problems with solutions and some exercises which follow the examples quite closely. In addition, problems are included which go beyond the examples, both in mathematical analysis and in the development of mathematical models for biological problems, in order to encourage deeper understanding and an eagerness to use mathematics in learning about biology.

The book is a comprehensive, self-contained introduction to the mathematical modeling and analysis of disease transmission models. It includes (i) an introduction to the main concepts of compartmental models including models with heterogeneous mixing of individuals and models for vector-transmitted diseases, (ii) a detailed analysis of models for important specific diseases, including tuberculosis, HIV/AIDS, influenza, Ebola virus disease, malaria, dengue fever and the Zika virus, (iii) an introduction to more advanced mathematical topics, including age structure, spatial structure, and mobility, and (iv) some challenges and opportunities for the future.

There are exercises of varying degrees of difficulty, and projects leading to new research directions. For the benefit of public health professionals whose contact with mathematics may not be recent, there is an appendix covering the necessary mathematical background. There are indications which sections require a strong mathematical background so that the book can be useful for both mathematical modelers and public health professionals.

Dynamical Systems for Biological Modeling: An Introduction prepares both biology and mathematics students with the understanding and techniques necessary to undertake basic modeling of biological systems. It achieves this through the development and analysis of dynamical systems.

The approach emphasizes qualitative ideas rather than explicit computations. Some technical details are necessary, but a qualitative approach emphasizing ideas is essential for understanding. The modeling approach helps students focus on essentials rather than extensive mathematical details, which is helpful for students whose primary interests are in sciences other than mathematics need or want.

The book discusses a variety of biological modeling topics, including population biology, epidemiology, immunology, intraspecies competition, harvesting, predator-prey systems, structured populations, and more.

The authors also include examples of problems with solutions and some exercises which follow the examples quite closely. In addition, problems are included which go beyond the examples, both in mathematical analysis and in the development of mathematical models for biological problems, in order to encourage deeper understanding and an eagerness to use mathematics in learning about biology.

As the world population exceeds the six billion mark, questions of population explosion, or how many people the earth can support, and under which conditions, become pressing. The goal of this book is to search for a balance between simple and analyzable models and unsolvable models which are capable of addressing questions such as these. This book, which will include both examples and exercises, will be useful to practitioners, graduate students, and scientists working in the field.

This self-contained textbook provides a comprehensive guide to the mathematical theory of disease transmission models. General theory is presented alongside models for specific diseases and related phenomena, with exposition that is accessible to those who are comfortable with calculus, elementary differential equations and linear algebra. The reader will gain insight into the modeling of: cross-immunity between different disease strains (such as influenza); synergistic interactions between multiple diseases (such as HIV and tuberculosis); diseases transmitted by viral agents, bacteria and vectors; and, both epidemic and endemic disease occurrences. This text is ideal for a graduate level course for students in mathematics, or for students of epidemiology with strong mathematics backgrounds. The material within will also be of interest to researchers in epidemiology and related areas, and those involved with the development of public health policy.

As the world population exceeds the six billion mark, questions of population explosion, or how many people the earth can support, and under which conditions, become pressing. The goal of this book is to search for a balance between simple and analyzable models and unsolvable models which are capable of addressing questions such as these. This book, which will include both examples and exercises, will be useful to practitioners, graduate students, and scientists working in the field.