Network analysis represents a valuable and flexible framework to understand the structure
of individual interactions at the population level in animal societies. The versatility of network …

Proximity social interactions are crucial for infectious diseases transmission. Crowded
agglomerations pose serious risk of triggering superspreading events. Locations like …

The dynamics of a spreading disease and individual behavioral changes are entangled
processes that have to be addressed together in order to effectively manage an outbreak …

Activity-driven networks are a powerful paradigm to study epidemic spreading over time-
varying networks. Despite significant advances, most of the current understanding relies on …

Network theory has greatly contributed to an improved understanding of epidemic
processes, offering an empowering framework for the analysis of real-world data, prediction …

Temporal networks have been increasingly used to model a diversity of systems that evolve
in time; for example, human contact structures over which dynamic processes such as …

Many datasets describing contacts in a population suffer from incompleteness due to
population sampling and underreporting of contacts. Data-driven simulations of spreading …

In the year 2020, there were 105 different statutory insurance companies in Germany with
heterogeneous regional coverage. Obtaining data from all insurance companies is …

Recent advances in data collection have facilitated the access to time-resolved human
proximity data that can conveniently be represented as temporal networks of contacts …

Editorial Network analysis and modelling: Special issue of European Journal of Applied
Mathematics Page 1 Euro. Jnl of Applied Mathematics (2016), vol. 27, pp. 807–811. c Cambridge …