| Literature DB >> 15094315 |
Ken T D Eames1, Matt J Keeling.
Abstract
Patterns of sexual mixing and heterogeneity in the number of sexual partners can have a huge effect on the spread of a sexually transmitted disease (STD). The sexual mixing network identifies all partnerships within a population over a given period and is a powerful tool in the study of such infections. Previous models assumed all links within the network to be concurrent active partnerships. We present a novel modelling approach in which we adapt the notion of a sexual contact network to a monogamous population by allowing the nature of the links to change. We use the underlying network to represent potential sexual partnerships, only some of which are active at any one time. Thus serial monogamy can be modelled while maintaining the patterns of mixing displayed by the population.Mesh:
Year: 2004 PMID: 15094315 DOI: 10.1016/j.mbs.2004.02.003
Source DB: PubMed Journal: Math Biosci ISSN: 0025-5564 Impact factor: 2.144