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

Authors :
Reid MC
Peebles K
Stansfield SE
Goodreau SM
Abernethy N
Gottlieb GS
Mittler JE
Herbeck JT
Source :
Vaccine [Vaccine] 2019 Aug 14; Vol. 37 (35), pp. 4886-4895. Date of Electronic Publication: 2019 Jul 12.
Publication Year :
2019

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.<br /> (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1873-2518
Volume :
37
Issue :
35
Database :
MEDLINE
Journal :
Vaccine
Publication Type :
Academic Journal
Accession number :
31307874
Full Text :
https://doi.org/10.1016/j.vaccine.2019.07.013