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This book covers recent developments in epidemic process models and related data on temporally varying networks.

This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for epidemic modeling, optimization of transportation and logistics, as well as understanding biological phenomena.Over the past 20 years, network theory has proven to be one of the most powerful tools for studying and analyzing...

This book offers an introduction to temporal network methods, which lift temporal information from the level of system dynamics to the mathematical representation of the contact network itself, yielding more accurate models of large-scale dynamic phenomena.

The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen.
Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach the temporal aspects are pre-encoded in the dynamic system model.
Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself.
This framework becomes particularly useful for...