Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/38038
Title: Identifying immunity gaps for measles using Belgian serial serology data
Authors: SCHENK, Julie 
ABRAMS, Steven 
Litzroth, Amber
Cornelissen , Laura
Grammens, Tine
Theeten, Heidi
HENS, Niel 
Issue Date: 2022
Publisher: ELSEVIER SCI LTD
Source: Vaccine, 40 (26) , p. 3676 -3683
Abstract: Vaccine-preventable diseases, such as measles, have been re-emerging in countries with moderate to high vaccine uptake. It is increasingly important to identify and close immunity gaps and increase coverage of routine childhood vaccinations, including two doses of the measles-mumps-rubella vaccine (MMR). Here, we present a simple cohort model relying on a Bayesian approach to evaluate the evolution of measles seroprevalence in Belgium using the three most recent cross-sectional serological survey data collections (2002, 2006 and 2013) and information regarding vaccine properties. We find measles seroprevalence profiles to be similar for the different regions in Belgium. These profiles exhibit a drop in seroprevalence in birth cohorts that were offered vaccination at suboptimal coverages in the first years after routine vaccination has been started up. This immunity gap is observed across all cross-sectional survey years, although it is more pronounced in survey year 2013. At present, the COVID-19 pandemic could negatively impact the immunization coverage worldwide, thereby increasing the need for additional immunization programs in groups of children that are impacted by this. Therefore, it is now even more important to identify existing immunity gaps and to sustain and reach vaccine-derived measles immunity goals. (C) 2022 The Authors. Published by Elsevier Ltd.
Notes: Schenk, J (corresponding author), UHasselt, Data Sci Inst, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Diepenbeek, Belgium.
julie.schenk@uhasselt.be
Keywords: Measles elimination;Bayesian MCMC;Serial serological survey data;Immunity goals
Document URI: http://hdl.handle.net/1942/38038
ISSN: 0264-410X
e-ISSN: 1873-2518
DOI: 10.1016/j.vaccine.2022.05.009
ISI #: 000836819800031
Rights: 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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