High prevalence regimes in the pair quenched mean-field theory for the susceptible-infected-susceptible model on networks
Diogo H. Silva, Francisco A. Rodrigues, Silvio C. Ferreira

TL;DR
This paper evaluates the pair quenched mean-field (PQMF) theory's accuracy in predicting SIS epidemic dynamics on networks, showing it outperforms standard QMF especially away from epidemic thresholds, with implications for high prevalence regimes.
Contribution
The study provides a comprehensive nonperturbative numerical analysis demonstrating the effectiveness of PQMF over QMF in diverse network structures for SIS models.
Findings
PQMF significantly outperforms QMF on synthetic networks.
PQMF provides highly accurate predictions away from epidemic thresholds.
Correlations between accuracy and average shortest path are observed.
Abstract
Reckoning of pairwise dynamical correlations significantly improves the accuracy of mean-field theories and plays an important role in the investigation of dynamical processes on complex networks. In this work, we perform a nonperturbative numerical analysis of the quenched mean-field theory (QMF) and the inclusion of dynamical correlations by means of the pair quenched mean-field (PQMF) theory for the susceptible-infected-susceptible (SIS) model on synthetic and real networks. We show that the PQMF considerably outperforms the standard QMF on synthetic networks of distinct levels of heterogeneity and degree correlations, providing extremely accurate predictions when the system is not too close to the epidemic threshold while the QMF theory deviates substantially from simulations for networks with a degree exponent . The scenario for real networks is more complicated, still…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
