rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Mathematics of Epidemics on Networks
    sub title: From Exact to Approximate Models
  name:
    name part: Kiss, István Z.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Miller, Joel C.
    role:
      role term: author.
  name:
    name part: Simon, Péter L.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVIII, 413 p. 130 illus., 89 illus. in color. online resource.
  abstract: This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks; Providing software that can solve the differential equation models or directly simulate epidemics in networks. Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and biology departments alike. .
  table of contents: 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.
  note: by István Z. Kiss, Joel C. Miller, Péter L. Simon.
  subject:
    topic: Mathematics
  subject:
    topic: Epidemiology
  subject:
    topic: Dynamics
  subject:
    topic: Ergodic theory
  subject:
    topic: Probabilities
  subject:
    topic: Biomathematics
  subject:
    topic: Mathematics
  subject:
    topic: Mathematical and Computational Biology
  subject:
    topic: Dynamical Systems and Ergodic Theory
  subject:
    topic: Applications of Graph Theory and Complex Networks
  subject:
    topic: Epidemiology
  subject:
    topic: Probability Theory and Stochastic Processes
  classification: QH323.5
  classification: QH324.2-324.25
  classification: 570.285
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Interdisciplinary Applied Mathematics, 46
  identifier: 9783319508061
  identifier: http://dx.doi.org/10.1007/978-3-319-50806-1
  record info:
    record creation date: 170608
    record change date: 20180306142843.0
    record identifier: 978-3-319-50806-1