2011/05/31 by Gregorio D’Agostino, Gregorio D'Agostino, Antonio Scala +2 · 3 citations
Computer Science · Mathematics · Medicine · Physics and Astronomy · #Assortative mating #Assortativity #Biology #COVID-19 epidemiological studies #Cascading failure #Complex Network Analysis Techniques #Complex network #Computer science #Econometrics #Economics #Epidemic model #Genetics #Medicine #Opinion Dynamics and Social Influence #Physics #Population #Quantum mechanics #Resilience (materials science) #Robustness (evolution) #Scale-free network #Statistical physics #cond-mat.dis-nn #cond-mat.stat-mech #cs.SI #physics.soc-ph
paper · pdf · doi:10.1209/0295-5075/97/68006
published as European Physics Letters, Vol. 97, No. 6 (March 2012) 68006 · 4 pages, 4 figures
openalex publication_date 2012/03/01 · arxiv created 2012/11/23 · arxiv updated 2012/11/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
By analysing the diffusive dynamics of epidemics and of distress in complex networks, we study the effect of the assortativity on the robustness of the networks. We first determine by spectral analysis the thresholds above which epidemics/failures can spread; we then calculate the slowest diffusional times. Our results shows that disassortative networks exhibit a higher epidemiological threshold and are therefore easier to immunize, while in assortative networks there is a longer time for intervention before epidemic/failure spreads. Moreover, we study by computer simulations the sandpile cascade model, a diffusive model of distress propagation (financial contagion). We show that, while assortative networks are more prone to the propagation of epidemic/failures, degree-targeted immunization policies increases their resilience to systemic risk.