Mathematical models for predicting the epidemiologic and economic impact of vaccination against human papillomavirus infection and disease

Abstract

Infection with human papillomavirus (HPV) is the primary cause of cervical cancer, other anogenital cancers, genital warts, and recurrent respiratory papillomatosis. Clinical studies have demonstrated that a prophylactic HPV vaccine can prevent infection, genital warts, and the precancerous lesions that lead to cervical cancer. Given the absence of data on the long-term effectiveness of HPV vaccination, a number of mathematical models have been developed to provide insight to policy makers by projecting the long-term epidemiologic and economic consequences of vaccination and evaluate alternative vaccination policies. This paper reviews the state of these models. Three types of HPV mathematical models have been reported in the literature: cohort, population dynamic, and hybrid. All have demonstrated that vaccination can significantly reduce the incidence of cervical cancer in the long term. However, only the cohort and hybrid models have evaluated the cost-effectiveness of vaccination strategies for preventing cervical cancer. These models have generally shown that vaccinating females can be cost-effective. None has accounted for the potential benefits of vaccinating the population to reduce the burden of recurrent respiratory papillomatosis and cancers of the vagina, vulva, anus, penis, and head/neck. Given that only the population dynamic model can account for both the direct and indirect (i.e., herd immunity effects) benefits of vaccination in the population, future research should focus on further development of dynamic models by expanding the range of epidemiologic outcomes tracked and including the ability to assess the cost-effectiveness of alternative vaccination policies.