Modelling Impact of Vaccination of Women Aged over 25 against Human Papillomaviruses Using Complex Networks

Abstract

This thesis proposes a sexual contact network growth model which produces scale-free contact network models using three mechanisms which reflect the real world relationship forming processes of people. The growth model is focused on heterosexual relationships and is calibrated to Australian demographics at present, though it can easily be adapted to other demographics. HPV transmission simulations are performed on the networks generated by the sexual contact network growth model and exemplify its utility to simulate HPV transmission. We consider the gender difference in seroreactivity and the interactions between different genotypes in transmission, which have not been studied in state-of-art computational HPV transmission models. Our analysis demonstrates that the network topology plays a considerate role in disease transmission, and a more connected network can encourage a more vigorous transmission. In addition, the simulation results suggest that coinfection with multiple types does not occur by chance, and the interactions between different genotypes will influence each other's transmission dynamics. We allocated HPV vaccination to the HPV transmission model, following the vaccination coverage distribution when HPV vaccines were firstly introduced to Australia. The analysis results demonstrate that on the premise of vaccinating adolescent girls and young females, improving the vaccination coverage in females aged 26-45 years can prevent HPV infection both on individual and population level.