This thesis sought to develop an agent-based model that replicates the formation of social and sexual partnerships in real-world settings with an eventual aim of revealing the main drivers of the HIV pandemic in a closed mixed society. Agent-based modelling is a computational modelling approach that allows for the simulation of the actions and interactions of autonomous agents, with the eventual objective of disovering global effects on the system. This modelling technique is less dependent on generalisations and does not average out the behaviour of individuals. Sexual partnerships formed in the model goes through the process of dating, courting and has a chance of developing into marriage as well as the possibility of breaking up or undergo divorce. Sexual partnership formation is based on a likeability index calculated using aspiration, attractiveness and age. Over and above the the sexual relationships we include commercial sex work. Commercial sex work depends mainly on the availability of female sex workers and their clients. We superimpose the spread of HIV on the social and sexual network model. Results from the model reveal that saturation of HIV prevalence is driven by the social and sexual network structure, behaviour change as well as biologic factors. Excluding commercial sex work in the model resulted in a decrease in HIV prevalence and incidence. Dense social networks resulted in a dense sexual network which consequently increased HIV incidence. A change in the infection probability per coital act contributed significantly to a change in incidence and prevalence levels. Model results also show that enrolling all HIV positive agents on antiretroviral therapy (ART) as from 2016 simulation year will help in curbing HIV transmission if zero dropout rate from ART is assumed. Therefore, on concomitant action to avoid dropouts from ART is necessary if full benefits of introducing ART to all HIV positive individuals are to be realised. / Operations Management / D.Phil. (Operations Research)