Mathematical Tools for Understanding Infectious Disease Dynamics
Language: English
Published by Princeton University Press, 2012
Series: Book 4 of 7 - Princeton Series in Theoretical and Computational Biology
- First Edition
- Hardcover
- New

Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.
AbeBooks seller since February 27, 2001
Condition: New
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- Title
- Mathematical Tools for Understanding Infectious Disease Dynamics
- Author
- Odo Diekmann
- Publisher
- Princeton University Press
- Publication year
- 2012
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0691155399
- ISBN 13
- 9780691155395
- Edition
- 1st Edition
- Series
- Book 4 of 7: Princeton Series in Theoretical and Computational Biology
Mathematical modeling is critical to our understanding of how infectious diseases spread at the individual and population levels. This book gives readers the necessary skills to correctly formulate and analyze mathematical models in infectious disease epidemiology, and is the first treatment of the subject to integrate deterministic and stochastic models and methods.
Mathematical Tools for Understanding Infectious Disease Dynamics fully explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology. This comprehensive and accessible book also features numerous detailed exercises throughout; full elaborations to all exercises are provided.
- Covers the latest research in mathematical modeling of infectious disease epidemiology
- Integrates deterministic and stochastic approaches
- Teaches skills in model construction, analysis, inference, and interpretation
- Features numerous exercises and their detailed elaborations
- Motivated by real-world applications throughout
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