English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We present a quenched mean-field (QMF) theory for the dynamics of thesusceptible-infected-susceptible (SIS) epidemic model on complex networks wheredynamical correlations between connected vertices are taken into account bymeans of a pair approximation. We present analytical expressions of theepidemic thresholds in the star and wheel graphs and in random regularnetworks. For random networks with a power law degree distribution, thethresholds are numerically determined via an eigenvalue problem. The pair andone-vertex QMF theories yield the same scaling for the thresholds as functionsof the network size. However, comparisons with quasi-stationary simulations ofthe SIS dynamics on large networks show that the former is quantitatively muchmore accurate than the latter. Our results demonstrate the central role playedby dynamical correlations on the epidemic spreading and introduce an efficientway to theoretically access the thresholds of very large networks that can beextended to dynamical processes in general.

Pair quenched mean-field theory for the susceptible-infected-susceptible model on complex networks