title: Dynamic concurrent partnership networks incorporating demography.
abstract: We introduce a population model that incorporates From a mathematical point of view we deal with continuous-time Markov chains at the individual level, with the interaction between individuals captured by a global variable describing opportunities for new partnerships. We show that for large time a stationary distribution is attained and we deduce various statistical features of that distribution, with particular attention for concurrency, i.e. the overlap in time of multiple partnerships of one and the same individual. Our ultimate motivation is to model the spread of sexually transmitted infections in the population, for which the present paper serves as a prelude.
authors.affiliation: Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands. K.Y.Leung@uu.nl
authors.forename: K Y
authors.initials: KY
authors.lastname: Leung
authors.forename: M E E
authors.initials: ME
authors.lastname: Kretzschmar
authors.forename: O
authors.initials: O
authors.lastname: Diekmann
mesh_terms: D003710:Demography; D006801:Humans; D008390:Markov Chains; D008962:Models, Theoretical; D011157:Population Dynamics