Overview
- Most detailed and broad treatment of stochastic epidemic models ever published in one volume
- Covers both classical and new results and methods, from mathematical models to statistical procedures
- Aimed at PhD students and Post Docs in mathematical sciences
- Includes numerous Examples and Exercises (some with solutions)
Part of the book series: Lecture Notes in Mathematics (LNM, volume 2255)
Part of the book sub series: Mathematical Biosciences Subseries (LNMBIOS)
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Table of contents (15 chapters)
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Front Matter
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Stochastic Epidemics in a Homogeneous Community
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Front Matter
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Back Matter
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Stochastic SIR Epidemics in Structured Populations
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Front Matter
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Back Matter
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Stochastic Epidemics in a Heterogeneous Community
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Front Matter
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Back Matter
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Statistical Inference for Epidemic Processes in a Homogeneous Community
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Front Matter
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Keywords
- Infectious disease
- Homogeneous models
- Two-level mixing models
- Epidemics on graphs
- statistics on epidemics models
- compartment models
- Basic reproduction number
- Final size of an epidemic
- Early stage of an epidemic outbreak
- Time to extinction
- Weak convergence
- Central Limit Theorem
- Coupling
- Large deviations
- SIR model on a configuration model random graph
- Household models
About this book
Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo).
The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.
Editors and Affiliations
About the editors
Etienne Pardoux is professor emeritus at the Institut de Mathématiques de Marseille, within Aix Marseille Univ. His research has covered several topics of stochastic analysis, in particular stochastic partial differential equations, backward stochastic differential equations and homogenization. More recently, he has turned his interests towards evolutionary biology and modeling of infectious diseases. He is the author of more than 160 publications, including four books.
Bibliographic Information
Book Title: Stochastic Epidemic Models with Inference
Editors: Tom Britton, Etienne Pardoux
Series Title: Lecture Notes in Mathematics
DOI: https://doi.org/10.1007/978-3-030-30900-8
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-30899-5Published: 01 December 2019
eBook ISBN: 978-3-030-30900-8Published: 30 November 2019
Series ISSN: 0075-8434
Series E-ISSN: 1617-9692
Edition Number: 1
Number of Pages: XVIII, 474
Number of Illustrations: 11 b/w illustrations, 17 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Epidemiology, Mathematical and Computational Biology