activity
20222026
most citedThe Fitness-Corrected Block Model, or how to create maximum-entropy data-driven spatial social networks

6 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SI20265 cited

Epidemics in a Synthetic Urban Population with Multiple Levels of Mixing

Alessandro Celestini, Francesca Colaiori, Stefano Guarino +2

Network--based epidemic models that account for heterogeneous contact patterns are extensively used to predict and control the diffusion of infectious diseases. We use census and s…

cs.SI2025

Random Hyperbolic Graphs with Arbitrary Mesoscale Structures

Stefano Guarino, Davide Torre, Enrico Mastrostefano

Real-world networks exhibit universal structural properties such as sparsity, small-worldness, heterogeneous degree distributions, high clustering, and community structures. Geomet…

physics.soc-ph20252 cited

When to Boost: How Dose Timing Determines the Epidemic Threshold

Alessandro Celestini, Francesca Colaiori, Stefano Guarino +3

Most vaccines require multiple doses, the first to induce recognition and antibody production and subsequent doses to boost the primary response and achieve optimal protection. We…

cs.SI2023

Scaling Expected Force: Efficient Identification of Key Nodes in Network-based Epidemic Models

Paolo Sylos Labini, Andrej Jurco, Matteo Ceccarello +3

Centrality measures are fundamental tools of network analysis as they highlight the key actors within the network. This study focuses on a newly proposed centrality measure, Expect…

physics.soc-ph20226 cited

The Fitness-Corrected Block Model, or how to create maximum-entropy data-driven spatial social networks

Massimo Bernaschi, Alessandro Celestini, Stefano Guarino +2

Models of networks play a major role in explaining and reproducing empirically observed patterns. Suitable models can be used to randomize an observed network while preserving some…