Human Papillomavirus (HPV) is a common infection that can lead to cancers, particularly cervical cancer. This thesis presents mathematical models to better understand the spread of HPV and the best strategies for preventing this infection and its serious consequences, such as cervical cancer.
The first model focuses on the dynamics of HPV transmission in the population and integrates prevention strategies such as public awareness campaigns and vaccination. The second model further examines the progression of HPV infection into precancerous lesions and, eventually, cancer. The analysis demonstrated that, under certain conditions, it is possible to significantly reduce the incidence of these cancers through better management of interventions.

The study highlights the importance of several factors, such as vaccination rates, awareness efforts, and access to screening. Numerical simulations showed that combined strategies such as awareness campaigns, vaccination of both women and men, and screening for precancerous lesions are the most effective in terms of cost and health impact.

The results of this research provide practical recommendations for public health decision-makers. In particular, it emphasizes the importance of targeting young populations for vaccination and improving access to care in low-income areas, where the burden of HPV is often higher.