Preface.- Introduction to Networks and Diseases.- Exact Propagation Models: Top Down.- Exact Propagation Models: Bottom-Up.- Mean-Field Approximations for Heterogeneous Networks.- Percolation-Based Approaches for Disease Modelling.- Hierarchies of SIR Models.- Dynamic and Adaptive Networks.- Non-Markovian Epidemics.- PDE Limits for Large Networks.- Disease Spread in Networks with Large-scale structure.- Appendix: Stochastic Simulation.- Index.
Dr. I.Z. Kiss: Dr. Kiss is a Reader in the Department of
Mathematics at the University of Sussex with his research at the
interface of network science, stochastic processes and dynamical
systems. His work focuses on the modeling and analysis of
stochastic epidemic processes on static and dynamic networks. His
current interests include the identification of rigorous links
between approximate models and their rigorous mathematical
counterparts and formulating new models for more complex spreading
processes or structured networks.
Dr. J.C. Miller: Dr. Miller is a Senior Research Scientist
at the Institute for Disease Modeling in Seattle. He is also
a Senior Lecturer at Monash University in Melbourne with a joint
appointment in Mathematics and Biology. His research interests
include dynamics of infectious diseases, stochastic processes on
networks, and fluid flow in porous media. The majority of his work
is at the intersection of infectious disease dynamics and
stochastic processes on networks.
Prof. P.L. Simon: Prof. Simon is a Professor at the
Institute of Mathematics, Eötvös Loránd University, Budapest. He is
a member of the Numerical Analysis and Large Networks research
group and the Head of Department of Applied Analysis and
Computational Mathematics. His research interests include dynamical
systems, partial differential equations and their applications in
chemistry and biology. In particular, his work focuses on the
modeling and analysis of network processes using differential
equations.
“The book adds to the knowledge of epidemic modeling on networks by
providing a number of rigorous mathematical arguments and
confirming the validity and optimal range of applicability of the
epidemic models. It serves as a good reference guide for
researchers and a comprehensive textbook for graduate students.”
(Yilun Shang, Mathematical Reviews, November, 2017)
“This is one of the first books to appear on modeling epidemics on
networks. … This is a comprehensive and well-written text aimed at
students with a serious interest in mathematical epidemiology. It
is most appropriate for strong advanced undergraduates or graduate
students with some background in differential equations, dynamical
systems, probability and stochastic processes.” (William J. Satzer,
MAA Reviews, September, 2017)
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