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Epidemics. 2015 Jun;11:32-47. doi: 10.1016/j.epidem.2015.01.003. Epub 2015 Feb 7.

Impact of coverage-dependent marginal costs on optimal HPV vaccination strategies.

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Department of Mathematics, Duke University, Durham, NC 27708, USA. Electronic address:
Department of Mathematics, Duke University, Durham, NC 27708, USA.
Department of Mathematics, Drake University, Des Moines, IA 50311, USA.
Department of Statistics, The Ohio State University, Columbus, OH 43210, USA; Department of Mathematics, The Ohio State University, Columbus, OH 43210, USA.
Department of Obstetrics and Gynecology, Duke University Medical School, Durham, NC 27708, USA.


The effectiveness of vaccinating males against the human papillomavirus (HPV) remains a controversial subject. Many existing studies conclude that increasing female coverage is more effective than diverting resources into male vaccination. Recently, several empirical studies on HPV immunization have been published, providing evidence of the fact that marginal vaccination costs increase with coverage. In this study, we use a stochastic agent-based modeling framework to revisit the male vaccination debate in light of these new findings. Within this framework, we assess the impact of coverage-dependent marginal costs of vaccine distribution on optimal immunization strategies against HPV. Focusing on the two scenarios of ongoing and new vaccination programs, we analyze different resource allocation policies and their effects on overall disease burden. Our results suggest that if the costs associated with vaccinating males are relatively close to those associated with vaccinating females, then coverage-dependent, increasing marginal costs may favor vaccination strategies that entail immunization of both genders. In particular, this study emphasizes the necessity for further empirical research on the nature of coverage-dependent vaccination costs.


Human papillomavirus vaccination; Male HPV vaccination; Marginal distribution costs; Optimal vaccine distribution; Stochastic agent-based models

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