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

Loading...
Thumbnail Image

Date

2015-06

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

688
views
291
downloads

Citation Stats

Abstract

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.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1016/j.epidem.2015.01.003

Publication Info

Ryser, MD, K McGoff, DP Herzog, DJ Sivakoff and ER Myers (2015). Impact of coverage-dependent marginal costs on optimal HPV vaccination strategies. Epidemics, 11. pp. 32–47. 10.1016/j.epidem.2015.01.003 Retrieved from https://hdl.handle.net/10161/9500.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Ryser

Marc Daniel Ryser

Associate Professor in Population Health Sciences

Marc D. Ryser conducts research in cancer early detection, with a particular focus on breast cancer overdiagnosis and overtreatment. Using a multi-scale approach, his group generates and analyzes biologic, clinical and population data using a variety of mathematical, statistical and computational tools. Dr. Ryser teaches an immersive research seminar for undergraduate students called “Math & Medicine.”

Website: https://sites.duke.edu/marcdryser/

Myers

Evan Robert Myers

Walter L. Thomas Distinguished Professor of Obstetrics and Gynecology in the School of Medicine

My research interests are broadly in the application of quantitative methods, especially mathematical modeling and decision analysis, to problems in women's health. Recent and current activities include integration of simulation modeling and systematic reviews to inform decisions surrounding cervical, ovarian, and breast cancer prevention and control, screening for postpartum depression, and management of uterine fibroids.    We are also engaged in exploring methods for integrating guidelines development and research prioritization.    In addition, I have ongoing collaborations using the tools of decision analysis with faculty in other clinical areas  Research is conducted through the Division of Reproductive Sciences in the Department of Obstetrics and Gynecology, the Evidence Synthesis Group in the Duke Clinical Research Institute, and the Duke Cancer Institute.  I'm also the course director for CRP 259, "Decision Sciences in Clinical Research", in Duke's Clinical Research Training Program.


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.