Mathematical Modeling for Epidemiology and Ecology 2nd ed.

Mathematical Modeling for Epidemiology and Ecology provides readers with the mathematical tools needed to understand and use mathematical models and read advanced mathematical biology books. It presents mathematics in biological contexts, focusing on the central mathematical ideas and the biological implications, with detailed explanations. The author assumes no mathematics background beyond elementary differential calculus.

An introductory chapter on basic principles of mathematical modeling is followed by chapters on empirical modeling and mechanistic modeling. These chapters contain a thorough treatment of key ideas and techniques that are often neglected in mathematics books, such as the Akaike Information Criterion. The second half of the book focuses on analysis of dynamical systems, emphasizing tools to simplify analysis, such as the Routh-Hurwitz conditions and asymptotic analysis. Courses can be focused on either half of the book or thematically chosen material from both halves, such as a course on mathematical epidemiology.

The biological content is self-contained and includes many topics in epidemiology and ecology. Some of this material appears in case studies that focus on a single detailed example, and some is based on recent research by the author on vaccination modeling and scenarios from the COVID-19 pandemic.

The problem sets feature linked problems where one biological setting appears in multi-step problems that are sorted into the appropriate section, allowing readers to gradually develop complete investigations of topics such as HIV immunology and harvesting of natural resources. Some problems use programs written by the author for Matlab or Octave; these combine with more traditional mathematical exercises to give students a full set of tools for model analysis. Each chapter contains additional case studies in the form of projects with detailed directions. New appendices contain mathematical details on optimization, numerical solution of differential equations, scaling, linearization, and sophisticated use of elementary algebra to simplify problems.

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Description

Mathematical Modeling for Epidemiology and Ecology (Springer Undergraduate Texts in Mathematics and Technology) 2nd ed.

By Glenn Ledder (Author)

Provides mathematical tools for understanding and using models in biological contexts.
Assumes no prior knowledge beyond elementary differential calculus.
Introductory chapter: Basic principles of mathematical modeling.
Chapters on:
- Empirical and mechanistic modeling, with a focus on key ideas often overlooked in traditional math texts (e.g., Akaike Information Criterion).
- Dynamical systems analysis, including tools like Routh-Hurwitz conditions and asymptotic analysis.
Focuses on biological applications, particularly in epidemiology and ecology.
Includes case studies on topics like vaccination modeling, HIV immunology, and COVID-19 scenarios.
Problem sets: Linked problems for gradual development of topic investigations.
Incorporates Matlab/Octave programs for model analysis.
Includes detailed projects and appendices covering optimization, differential equations, scaling, linearization, and problem simplification.
Suitable for courses on mathematical modeling, mathematical epidemiology, and related fields.

Mathematical Modeling for Epidemiology and Ecology (Springer Undergraduate Texts in Mathematics and Technology) 2nd ed. available at Book delivery.com for home delivery and cash on delivery all over Pakistan. You can contact for all kind of Medical Books.