Epidemics scenarios in the "Romantic network"

• Published in: arXiv.org 2012-08
• Main Authors: Carvalho, Alexsandro M, Goncalves, Sebastian
• Format: Article
• Language: English
• Subjects: Diffusion effects; Epidemics; Outbreaks; Propagation; Route selection; Topology
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1208.2609

The structure of sexual contacts, its contacts network and its temporal interactions, play an important role in the spread of sexually transmitted infections. Unfortunately, that kind of data is very hard to obtain. One of the few exceptions is the "Romantic network" which is a complete structure of a real sexual network of a high school. In terms of topology, unlike other sexual networks classified as scale-free network. Regarding the temporal structure, several studies indicate that relationship timing can have effects on diffusion through networks, as relationship order determines transmission routes.With the aim to check if the particular structure, static and dynamic, of the Romantic network is determinant for the propagation of an STI in it, we perform simulations in two scenarios: the static network where all contacts are available and the dynamic case where contacts evolve in time. In the static case, we compare the epidemic results in the Romantic network with some paradigmatic topologies. We further study the behavior of the epidemic on the Romantic network in response to the effect of any individual, belonging to the network, having a contact with an external infected subject, the influence of the degree of the initial infected, and the effect of the variability of contacts per unit time. We also consider the dynamics of formation of pairs in and we study the propagation of the diseases in this dynamic scenario. Our results suggest that while the Romantic network can not be labeled as a Watts-Strogatz network, it is, regarding the propagation of an STI, very close to one with high disorder. Our simulations confirm that relationship timing affects, but strongly lowering, the final outbreak size. Besides, shows a clear correlation between the average degree and the outbreak size over time.