collaborators

5 papers

physics.soc-ph2026

A principled closure framework for higher-order SIS epidemic models on networks

Kevin Teo, Peter L Simon, István Zoltán Kiss

Susceptible-infected-susceptible (SIS) epidemic models on networks are governed by hierarchical moment equations where the dynamics of smaller subsystems depend on the state of lar…

physics.soc-ph2026

Edge-based mean-field approximation of dynamics on networks via approximate lumping of Markov chains

Gábor Timár, Jonathan A. Ward, Péter L. Simon

Mean-field approximations for dynamical processes on networks are widely used, but existing derivations often rely either on moment closures or on idealised assumptions about netwo…

physics.soc-ph2026

To trace or not to trace: analytical insights from network-based contact-tracing models

Giulia de Meijere, Andrea Pugliese, Gerardo Iñiguez +2

Contact tracing is one of the most important control measures deployed during epidemics. Relying on the identification of contacts of known infected individuals, it necessitates a…

physics.soc-ph2025

On the accuracy of population level approximation of network processes

Noémi Nagy, Sándor Horváth, Balázs Maga +1

The individual-based model of simple contagion processes is considered on regular graphs. This model explicitly incorporates the adjacency matrix of the network enabling us to stud…

math.PR2025

Mean-Field Approximation of Dynamics on Networks

Jonathan A. Ward, Gábor Timár, Péter L. Simon

Many real-world phenomena can be modelled as dynamical processes on networks, a prominent example being the spread of infectious diseases such as COVID-19. Mean-field approximation…