title: A versatile ODE approximation to a network model for the spread of sexually transmitted diseases.
abstract: We develop a moment closure approximation (MCA) to a network model of sexually transmitted disease (STD) spread through a steady/casual partnership network. MCA has been used previously to approximate static, regular lattices, whereas application to dynamic, irregular networks is a new endeavour, and application to sociologically-motivated network models has not been attempted. Our goals are 1). to investigate issues relating to the application of moment closure approximations to dynamic and irregular networks, and 2). to understand the impact of concurrent casual partnerships on STD transmission through a population of predominantly steady monogamous partnerships. We are able to derive a moment closure approximation for a dynamic irregular network representing sexual partnership dynamics, however, we are forced to use a triple approximation due to the large error of the standard pair approximation. This example underscores the importance of doing error analysis for moment closure approximations. We also find that a small number of casual partnerships drastically increases the prevalence and rate of spread of the epidemic. Finally, although the approximation is derived for a specific network model, we can recover approximations to a broad range of network models simply by varying model parameters which control the structure of the dynamic network. Thus our moment closure approximation is very flexible in the kinds of network models it can approximate.
authors.affiliation: Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario L8S 4K1, Canada. bauch@math.mcmaster.ca
authors.forename: C T
authors.initials: CT
authors.lastname: Bauch
mesh_terms: D003198:Computer Simulation; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D012725:Sexual Behavior; D012747:Sexual Partners; D012749:Sexually Transmitted Diseases / Q000453:epidemiology / Q000635:transmission*; D013269:Stochastic Processes