English

Modeling epidemics on d-cliqued graphs

Populations and Evolution 2019-05-24 v1 Social and Information Networks

Abstract

Since social interactions have been shown to lead to symmetric clusters, we propose here that symmetries play a key role in epidemic modeling. Mathematical models on d-ary tree graphs were recently shown to be particularly effective for modeling epidemics in simple networks [Seibold & Callender, 2016]. To account for symmetric relations, we generalize this to a new type of networks modeled on d-cliqued tree graphs, which are obtained by adding edges to regular d-trees to form d-cliques. This setting gives a more realistic model for epidemic outbreaks originating, for example, within a family or classroom and which could reach a population by transmission via children in schools. Specifically, we quantify how an infection starting in a clique (e.g. family) can reach other cliques through the body of the graph (e.g. public places). Moreover, we propose and study the notion of a safe zone, a subset that has a negligible probability of infection.

Keywords

Cite

@article{arxiv.1802.00102,
  title  = {Modeling epidemics on d-cliqued graphs},
  author = {Laura P. Schaposnik and Anlin Zhang},
  journal= {arXiv preprint arXiv:1802.00102},
  year   = {2019}
}

Comments

11 pages, 16 figures

R2 v1 2026-06-23T00:06:57.074Z