Mathematical Tools for Understanding Infectious Disease Dynamics

Odo Diekmann; Hans Heesterbeek; Tom Britton

Odo Diekmann, Hans Heesterbeek and Tom Britton

Mathematical Tools for Understanding Infectious Disease Dynamics

In: Princeton Series in Theoretical and Computational Biology, 7

Princeton University Press | 2013

https://doi.org/10.1515/9781400845620

Overview
Contents

About this book

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

Author information

Odo Diekmann is professor of mathematical analysis at Utrecht University. Hans Heesterbeek is professor of theoretical epidemiology at Utrecht University. Tom Britton is professor of mathematical statistics at Stockholm University.

Reviews

"This landmark volume describes for readers how one should view the theoretical side of mathematical epidemiology as a whole. A particularly important need is for a book that integrates deterministic and stochastic epidemiological models, and this is the first one that does this. I know of no better overview of the subject. It belongs on the shelf of everyone working in mathematical epidemiology."—Fred Brauer, University of British Columbia

This book will soon be a classic in the theoretical epidemiology and modeling literature.---Mirjam Kretzschmar, Biometrical Journal

The overtly pedagogical features of this text make it an outstanding choice for someone trying to learn the basic tools of the trade. The mathematician who makes a serious study of this text will be in an excellent position to work fruitfully with biologists or epidemiologists on either theoretical or data-driven problems of disease transmission.---Carl A. Toews, Mathematical Reviews

A much needed book. Mathematical Tools for Understanding Infectious Disease Dynamics is a welcome addition to the current literature and will hopefully help to unify the many different views in the field.---Laura Matrajt, SIAM Review

Frontmatter Free access PDF PDF	i
Contents Free access PDF PDF	vii
Preface Access restricted Content is available PDF PDF	xi
Part I. The bare bones: Basic issues in the simplest context Access restricted Content is available PDF PDF	1
Part II. Structured populations Access restricted Content is available PDF PDF	151
Part III. Case studies on inference Access restricted Content is available PDF PDF	307
Part IV. Elaborations Access restricted Content is available PDF PDF	347
Bibliography Access restricted Content is available PDF PDF	491
Index Access restricted Content is available PDF PDF	497

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Mathematical Tools for Understanding Infectious Disease Dynamics

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