A dynamic network model to disentangle the roles of steady and casual partners for HIV transmission among MSM

Abstract

HIV is a sexually transmitted infection (STI) whose transmission process is highly dependent on the sexual network structure of the population under consideration. Most sexual behaviour data is egocentric in nature. We develop a stochastic dynamic sexual network model that utilises this type of egocentric network data. The model incorporates both steady and casual sex partners, and can be seen as a stochastic form of a generalised pair-formation model. We model the spread of an infection where individuals are susceptible, infectious, or successfully treated (and unable to transmit) and derive analytical expressions for several epidemiological quantities. We use sexual behaviour and HIV prevalence data that was gathered among 403 MSM at an STI clinic in Stockholm. To accurately capture transmission dynamics for this population, we need to explicitly model both casual sex partners and steady partnerships. Our model yields an estimate for the mean time until diagnosis followed by successful treatment that is in line with literature. This study indicates that small reductions in the time to diagnosis, and thereby, beginning of treatment, may substantially reduce HIV prevalence. Moreover, we find that moderate increases in condom use with casual sex partners have greater impact on reducing prevalence than the same increases in condom use with steady sex partners. This result demonstrates the relative importance of casual contacts on the HIV transmission dynamics among MSM in Sweden. Our results highlight the importance of HIV testing and condom-use interventions, and the role that casual and steady partners play in this, in order to turn the epidemiological trend in Sweden towards decreased HIV incidence. Keywords: Mathematical models, Dynamic networks, Sexual behaviour, HIV, Steady and casual partners