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Academic & Professional Books  Reference  Data Analysis & Modelling  Modelling

Mathematics in Population Biology

By: Horst R Thieme
543 pages, 28 figs
Mathematics in Population Biology
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  • Mathematics in Population Biology ISBN: 9780691092911 Paperback Aug 2003 Usually dispatched within 4 days
  • Mathematics in Population Biology ISBN: 9780691092904 Hardback Dec 2003 Out of Print #137556
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About this book

Overview and selected sample of the results and ideas formed from the formulation, analysis, and re-evaluation of mathematical models in population biology. Organized by biological theme rather than mathematical concept. Uses well-chosen and varied examples to help develop appropriate modelling skills. Part I starts with unstructured single species population models, particularly in the framework of continuous time models, then adding the most rudimentary stage structure with variable stage duration. Part II develops the theme of stage structure in an age-dependant context, covering demographic concepts, such as life expectation and variance of life length, and their dynamic consequences. Part III considers the dynamic interplay of host and parasite populations, i.e., the epidemics and endemics of infectious diseases. The theme of stage structure continues in the analysis of different stages of infection and of age-structure that is instrumental in optimizing vaccination strategies.

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Horst R. Thieme is Professor of Mathematics at Arizona State University. He has published more than seventy research papers and is an associate editor of the "Journal of Mathematical Analysis and Applications". .
By: Horst R Thieme
543 pages, 28 figs
Media reviews
Mathematics in Population Biology provides a rigorous mathematical treatment of a wide variety of [models]. The attention to mathematical details is emphasized much more in this book than in many other popular mathematical biology textbooks and will be of particular interest to mathematicians... In addition, this book is an excellent reference for researchers interested in learning more about the mathematics behind the models of population biology. -- Linda J. S. Allen SIAM Review
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