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Vaccine. 2019 Aug 14;37(35):4886-4895. doi: 10.1016/j.vaccine.2019.07.013. Epub 2019 Jul 12.

Models to predict the public health impact of vaccine resistance: A systematic review.

Author information

1
Department of Epidemiology, 1959 NE Pacific Street, Magnuson Health Sciences Center, Room F-262, Seattle, WA 98195, United States; International Clinical Research Center, Department of Global Health, 908 Jefferson St., Seattle, WA 98104, United States. Electronic address: mollyr6@uw.edu.
2
Department of Epidemiology, 1959 NE Pacific Street, Magnuson Health Sciences Center, Room F-262, Seattle, WA 98195, United States; International Clinical Research Center, Department of Global Health, 908 Jefferson St., Seattle, WA 98104, United States. Electronic address: kpeebles@uw.edu.
3
Department of Epidemiology, 1959 NE Pacific Street, Magnuson Health Sciences Center, Room F-262, Seattle, WA 98195, United States; Department of Anthropologym Denny Hall, University of Washington, Seattle, WA 98195, United States. Electronic address: sestans@uw.edu.
4
Department of Epidemiology, 1959 NE Pacific Street, Magnuson Health Sciences Center, Room F-262, Seattle, WA 98195, United States; Department of Anthropologym Denny Hall, University of Washington, Seattle, WA 98195, United States. Electronic address: goodreau@uw.edu.
5
Department of Biomedical Informatics and Medical Education, University of Washington, Box 358047, Seattle, WA 98195, United States; Department of Health Services, 1959 NE Pacific St, Magnuson Health Sciences Center, Room H-680, Seattle, WA 98195-7660, United States. Electronic address: neila@uw.edu.
6
Division of Allergy and Infectious Diseases & Center for Emerging & Re-Emerging Infectious Diseases, Department of Medicine & Department of Global Health, 750 Republican St., Building E, Seattle, WA 98109, United States. Electronic address: gottlieb@uw.edu.
7
Department of Microbiology, 750 Republican St., Building F, Seattle, WA 98109, United States. Electronic address: jmittler@uw.edu.
8
International Clinical Research Center, Department of Global Health, 908 Jefferson St., Seattle, WA 98104, United States. Electronic address: herbeck@uw.edu.

Abstract

Pathogen evolution is a potential threat to the long-term benefits provided by public health vaccination campaigns. Mathematical modeling can be a powerful tool to examine the forces responsible for the development of vaccine resistance and to predict its public health implications. We conducted a systematic review of existing literature to understand the construction and application of vaccine resistance models. We identified 26 studies that modeled the public health impact of vaccine resistance for 12 different pathogens. Most models predicted that vaccines would reduce overall disease burden in spite of evolution of vaccine resistance. Relatively few pathogens and populations for which vaccine resistance may be problematic were covered in the reviewed studies, with low- and middle-income countries particularly under-represented. We discuss the key components of model design, as well as patterns of model predictions.

KEYWORDS:

Mathematical modeling; Vaccine resistance

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