scholarly journals Universality classes of the generalized epidemic process on random networks

2016 ◽  
Vol 93 (5) ◽  
Author(s):  
Kihong Chung ◽  
Yongjoo Baek ◽  
Meesoon Ha ◽  
Hawoong Jeong
2020 ◽  
Vol 19 (2) ◽  
pp. 56-62
Author(s):  
M. I. Gritsay ◽  
M. A. Koroleva ◽  
N. N. Fomkina ◽  
I. S. Koroleva

Aims. The purpose of this study was to identify current epidemiological features of meningococcal infection in Moscow.Materials and methods. Cases of invasive meningococcal disease in Moscow from 2014 to 2018 and the biomaterial from patients with an invasive meningococcal disease were analyzed.Results. The features of the epidemic process of meningococcal disease in Moscow were revealed: increasing in the incidence rate involving teenagers and young adults into the epidemic process; meningococcal strains of serogroups W and A increased in the etiology of the invasive meningococcal disease; high mortality rate.Conclusions. It seems reasonable to recommend vaccination against meningococcal disease by including adolescents, young adults and persons over 65 years old.


Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 976
Author(s):  
R. Aguilar-Sánchez ◽  
J. Méndez-Bermúdez ◽  
José Rodríguez ◽  
José Sigarreta

We perform a detailed computational study of the recently introduced Sombor indices on random networks. Specifically, we apply Sombor indices on three models of random networks: Erdös-Rényi networks, random geometric graphs, and bipartite random networks. Within a statistical random matrix theory approach, we show that the average values of Sombor indices, normalized to the order of the network, scale with the average degree. Moreover, we discuss the application of average Sombor indices as complexity measures of random networks and, as a consequence, we show that selected normalized Sombor indices are highly correlated with the Shannon entropy of the eigenvectors of the adjacency matrix.


2021 ◽  
Vol 127 (3) ◽  
Author(s):  
M. Dupont ◽  
Y. O. Kvashnin ◽  
M. Shiranzaei ◽  
J. Fransson ◽  
N. Laflorencie ◽  
...  

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