Personal contact networks are used to represent the social connections that exist between individuals within a population. Producing accurate networks that represent the actual vectors of infection that exist within a network can be useful for modelling epidemic trajectory and outcomes, which is significantly impacted by a network's structure. An evolutionary algorithm is used to evolve these networks subject to two fitness measures: epidemic duration and epidemic spread through a population. With each infection there is a small probability of a new variant being generated. Being infected with one variant provides partial immunity to future variants. This allows us to evaluate the impact of each variant, a significant innovation in comparison to other work. The amount by which each variant was allowed to change had a significant impact upon epidemic spread. For epidemic duration, the probability of new variants was the primary cause of increased epidemic duration.