Each year, more than 25,000 cases of invasive cancer attributable to human papillomavirus (HPV) infection occur in the United States; nearly 50% are cervical cancer, while the rest involve the oral cavity/oropharynx, anus, vulva, penis, and vagina. Collectively, these account for substantial morbidity and mortality, contribute to health disparities, and are associated with high economic costs. Advancements in HPV-related cancer epidemiology, coupled with new (e.g., HPV-16,-18 vaccines, HPV DNA testing) and emerging (e.g., biomarkers, therapeutic vaccines) technologies provide a remarkable opportunity to improve cancer prevention efforts. However, critical challenges remain with respect to clinical decision-making and prevention policy, pertaining to knowledge gaps and heterogeneities in the natural history of different cancers, uncertainties in HPV type distribution following HPV-16,-18 vaccination, and the real-world clinical effectiveness of emerging technologies. We propose to employ a decision-analytic approach, developing a flexible modeling framework that will allow us to synthesize the best available data; evaluate the health and economic consequences of alternative strategies; explore the uncertainty around their outcomes; explicitly quantify the tradeoffs associated with different approaches; and inform timely clinical and policy questions. By achieving our aims, we expect to have an impact on (1) the analytic methods of decision science; (2) the equitable distribution and rationale use of new technology; (3) the effectiveness of strategies for cancer prevention through clinical guidelines and national policies; (4) HPV-related cancer outcomes, including reduced incidence, enhanced quality of life, improved survival, and reduced disparities; and (5) the financial and economic profile of delivering cancer-related health services. PUBLIC HEALTH RELEVANCE: Rapid advances in the fields of HPV-related cancer epidemiology and medical technology present opportunities to revolutionize the approach to cancer prevention in the U.S. but have outpaced the ability of policy makers to make informed decisions regarding optimal adoption of health interventions. In this project, we propose to develop a flexible modeling framework that will enable us to synthesize the best available data on HPV, provide insight into the comparative and cost-effectiveness of different strategies, and assist in informed public health and clinical decision-making with respect to prevention of HPV-related cancers.