Epidemics on a weighted network with tunable degree-degree correlation
2014 (English)In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 253, 40-49 p.Article in journal (Refereed) Published
We propose a weighted version of the standard configuration model which allows for a tunable degree-degree correlation. A social network is modeled by a weighted graph generated by this model, where the edge weights indicate the intensity or type of contact between the individuals. An inhomogeneous Reed-Frost epidemic model is then defined on the network, where the inhomogeneity refers to different disease transmission probabilities related to the edge weights. By tuning the model we study the impact of different correlation patterns on the network and epidemics therein. Our results suggest that the basic reproduction number R-0 of the epidemic increases (decreases) when the degree-degree correlation coefficient rho increases (decreases). Furthermore, we show that such effect can be amplified or mitigated depending on the relation between degree and weight distributions as well as the choice of the disease transmission probabilities. In addition, for a more general model allowing additional heterogeneity in the disease transmission probabilities we show that rho can have the opposite effect on R-0.
Place, publisher, year, edition, pages
2014. Vol. 253, 40-49 p.
Branching processes, Configuration model, Weighted graph, Epidemic threshold, Degree-degree correlation
IdentifiersURN: urn:nbn:se:su:diva-106327DOI: 10.1016/j.mbs.2014.03.013ISI: 000337874100006OAI: oai:DiVA.org:su-106327DiVA: diva2:736555