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• W2509348029 abstract "We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general network-based measures derived from random walks theory. Using the daily air-traffic transportation data we perform numerical experiments to compare the infection arrival time with this alternative metric that is obtained by accounting for multiple walks instead of only the most probable path. The comparison with direct simulations reveals a higher correlation compared to the shortest-path approach used previously. In addition our method allows to connect fundamental observables in epidemic spreading with the cumulant-generating function of the hitting time for a Markov chain. Our results provides a general and computationally efficient approach using only algebraic methods." @default.
• W2509348029 created "2016-09-16" @default.
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• W2509348029 date "2017-01-17" @default.
• W2509348029 modified "2023-10-11" @default.
• W2509348029 title "Effective distances for epidemics spreading on complex networks" @default.
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• W2509348029 doi "https://doi.org/10.1103/physreve.95.012313" @default.
• W2509348029 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7217543" @default.
• W2509348029 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28208446" @default.
• W2509348029 hasPublicationYear "2017" @default.
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