| Full text | |
| Author(s): |
Iannelli, Flavio
;
Koher, Andreas
;
Brockmann, Dirk
;
Hoevel, Philipp
;
Sokolov, Igor M.
Total Authors: 5
|
| Document type: | Journal article |
| Source: | Physical Review E; v. 95, n. 1 JAN 17 2017. |
| Web of Science Citations: | 19 |
| 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. (AU) | |
| FAPESP's process: | 15/50122-0 - Dynamic phenomena in complex networks: basics and applications |
| Grantee: | Elbert Einstein Nehrer Macau |
| Support type: | Research Projects - Thematic Grants |