| Traditionally, disease transmission is described by homogeneous mixing models, which assume that individuals have a random and equal chance of infecting any person in the population. However, sexually transmitted infections are spread through sexual partnerships and pair dynamics may play an important role in transmission models for human papillomavirus (HPV), which causes cervical cancer. This thesis examines an ODE "pair model" and a sexual partnership network model investigating the importance of including pair dynamics. It is found that the relevance of pair dynamics depends on how the model is analyzed. In general, for a given transmission rate, disease prevalence is higher when partnership dynamics are not included. Although, if the transmission rate is calibrated to match observed prevalence, the predicted impact of vaccination is the same regardless of whether partnerships are included. Thus, the significance of including pair dynamics depends on what is investigated and which experiments are implemented. |
