Social Clustering in Epidemic Spread on Coevolving Networks

Abstract

Even though transitivity is a central structural feature of social networks, its influence on epidemic spread on coevolving networks has remained relatively unexplored. Here we introduce and study an adaptive SIS epidemic model wherein the infection and network coevolve with non-trivial probability to close triangles during edge rewiring, leading to substantial reinforcement of network transitivity. This new model provides a unique opportunity to study the role of transitivity in altering the SIS dynamics on a coevolving network. Using numerical simulations and Approximate Master Equations (AME), we identify and examine a rich set of dynamical features in the new model. In many cases, the AME including transitivity reinforcement provides accurate predictions of stationary-state disease prevalences and network degree distributions. Furthermore, for some parameter settings, the AME accurately trace the temporal evolution of the system. We show that higher transitivity reinforcement in the model leads to lower levels of infective individuals in the population, when closing a triangle is the dominant rewiring mechanism. These methods and results may be useful in developing ideas and modeling strategies for controlling SIS type epidemics.

arXiv comment16 pages, 21 figures

References in corpus (27)

• The spread of epidemic disease on networks
• Forecast and Control of Epidemics in a Globalized World
• Epidemics and percolation in small-world networks
• Epidemic dynamics on an adaptive network
• Adaptive Coevolutionary Networks: A Review
• Small But Slow World: How Network Topology and Burstiness Slow Down Spreading
• Nonequilibrium phase transition in the coevolution of networks and opinions
• Small world effect in an epidemiological model
• Random graphs with clustering
• Impact of non-Poisson activity patterns on spreading processes
• Epidemic thresholds of the Susceptible-Infected-Susceptible model on networks: A comparison of numerical and theoretical results
• Fluctuating epidemics on adaptive networks
• High-accuracy approximation of binary-state dynamics on networks
• Adaptive networks: coevolution of disease and topology
• Modeling complex systems with adaptive networks
• Binary-state dynamics on complex networks: pair approximation and beyond
• The unreasonable effectiveness of tree-based theory for networks with clustering
• Bond percolation on a class of clustered random networks
• Prudent behaviour accelerates disease transmission
• How memory generates heterogeneous dynamics in temporal networks
• Birth and death of links control disease spreading in empirical contact networks
• Epidemic spreading on evolving signed networks
• Evolutionary prisoner's dilemma games coevolving on adaptive networks
• Dynamical origins of the community structure of multi-layer societies
• Transitivity reinforcement in the coevolving voter model
• Role of social environment and social clustering in spread of opinions in co-evolving networks
• Link-based formalism for time evolution of adaptive networks

Cited by in corpus (3)

• Multilayer modeling of adoption dynamics in energy demand management
• Co-evolution of Viral Processes and Structural Stability in Signed Social Networks
• Local Symmetry and Global Structure in Adaptive Voter Models