Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

Epidemic centrality – identifying “superspreaders” in complex networks (CROSBI ID 580531)

Prilog sa skupa u zborniku | sažetak izlaganja sa skupa

Šikić, Mile ; Lančić, Alen ; Antulov-Fantulin, Nino ; Štefančić, Hrvoje Epidemic centrality – identifying “superspreaders” in complex networks // Book of Abstracts ECCS'11 Vienna / Thurner, Stefan ; Szell, Michael (ur.). Beč, 2011. str. 124-125

Podaci o odgovornosti

Šikić, Mile ; Lančić, Alen ; Antulov-Fantulin, Nino ; Štefančić, Hrvoje

engleski

Epidemic centrality – identifying “superspreaders” in complex networks

In the study of disease spreading on empirical complex networks in SIR model, initially infected nodes can be ranked according to some measure of their epidemic impact. The highest ranked nodes, also referred to as ``superspreaders" are associated to dominant epidemic risks and therefore deserve special attention. In simulations on studied empirical complex networks it is shown that the ranking depends on the dynamical regime of the disease spreading. A possible mechanism leading to this dynamical dependence is illustrated in an analytically tractable example. In systems where the allocation of resources to counter disease spreading to individual nodes is based on their ranking, the dynamical regime of disease spreading is frequently not known before the outbreak of the disease. Therefore we introduce a quantity called {; ; \em epidemic centrality}; ; as an average over all regimes of disease spreading as a basis of the ranking. A recently introduced concept of phase diagram of epidemic spreading is used as a framework in which several types of averaging are studied. The epidemic centrality is compared to structural properties of nodes such as node degree, k-cores and betweenness. There is a growing trend of epidemic centrality with degree and k-cores values, but the variation of epidemic centrality is much smaller than the variation of degree or k-cores value. It is found that the epidemic centrality of the structurally peripheral nodes is of the same order of magnitude as the epidemic centrality of the structurally central nodes. The implications of these findings for the distributions of resources to counter disease spreading are discussed.

complex networks; SIR model; epidemic centrality; epidemiology

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o prilogu

124-125.

2011.

objavljeno

Podaci o matičnoj publikaciji

Book of Abstracts ECCS'11 Vienna

Thurner, Stefan ; Szell, Michael

Beč:

978-3-85409-613-9

Podaci o skupu

European Conference on Complex Systems 2011

poster

12.09.2011-16.09.2011

Beč, Austrija

Povezanost rada

Fizika, Računarstvo

Poveznice