Immunogenicity and persistence of trivalent measles, mumps, and rubella vaccines: a systematic review and meta-analysis
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Published on: February 22, 2019
Julie Schenk1, Steven Abrams2, Heidi Theeten3
1Data Science Institute, I-BioStat, UHasselt, Diepenbeek, Belgium.
Background:
Despite the universal use of the two-dose trivalent measles-mumps-rubella (MMR) vaccine in the past two decades, outbreaks of these diseases still occur in countries with high vaccine uptake, giving rise to concerns about primary and secondary failure of MMR vaccine components. We aimed to provide seroconversion and waning rate estimates for the measles, mumps, and rubella components of MMR vaccines.
Methods:
In this systematic review and meta-analysis we searched PubMed (including MEDLINE), Web of Science, and Embase for randomised controlled trials, cohort studies, or longitudinal studies reporting the immunogenicity and persistence of MMR vaccines, published in English from database inception to Dec 31, 2019. Studies were included if they investigated vaccine-induced immunity in healthy individuals who received a trivalent MMR vaccine, including different dosages and timepoints of vaccine administration. Studies featuring coadministration of MMR with other vaccines, maternal immunity to the MMR vaccine, or non-trivalent formulations of the vaccine were excluded. Pooled seroconversion and waning rates were estimated by random-effects meta-analyses. This study is registered with PROSPERO, CRD42019116705.
Findings:
We identified 3615 unique studies, 62 (1·7%) of which were eligible for analysis. Estimated overall seroconversion rates were 96·0% (95% CI 94·5-97·4; I2=91·1%) for measles, 93·3% (91·1-95·2; I2=94·9%) for mumps when excluding the Rubini strain, 91·1% (87·4-94·1; I2=96·6%) for mumps when including the Rubini strain, and 98·3% (97·3-99·2; I2=93·0%) for rubella. Estimated overall annual waning rates were 0·009 (95% CI 0·005-0·016; I2=85·2%) for measles, 0·024 (0·016-0·039; I2=94·7%) for mumps, and 0·012 (0·010-0·014; I2=93·3%) for rubella.
Interpretation:
Our meta-analysis provides estimates of primary and secondary vaccine failure, which are essential to improve the accuracy of mathematical and statistical modelling to understand and predict the occurrence of future measles, mumps, and rubella outbreaks in countries with high vaccine uptake.
Funding:
European Research Council.
Insights
This study estimates measles-mumps-rubella (MMR) vaccine effectiveness, finding high seroconversion rates but also identifying waning immunity. These findings are crucial for predicting future outbreaks in highly vaccinated populations.
Area of Science:
- Immunology
- Vaccinology
- Epidemiology
Background:
- Measles-mumps-rubella (MMR) vaccine is widely used, yet outbreaks persist in highly vaccinated areas.
- Concerns exist regarding primary and secondary vaccine failure of MMR components.
- This study addresses the need for robust data on MMR vaccine immunogenicity and durability.
Purpose of the Study:
- To estimate seroconversion rates for measles, mumps, and rubella components of the MMR vaccine.
- To determine the rate of waning immunity for each component of the MMR vaccine.
- To provide data for improved modeling of disease outbreaks.
Main Methods:
- Systematic review and meta-analysis of randomized controlled trials, cohort studies, and longitudinal studies.
- Searched PubMed, Web of Science, and Embase for studies published up to December 31, 2019.
- Included studies on healthy individuals receiving trivalent MMR vaccine; excluded co-administration, maternal immunity, or non-trivalent formulations.
Main Results:
- Estimated seroconversion rates: measles 96.0%, mumps 93.3% (excluding Rubini strain) or 91.1% (including Rubini strain), and rubella 98.3%.
- Estimated annual waning rates: measles 0.009, mumps 0.024, and rubella 0.012.
- Included 62 eligible studies from an initial 3615 unique studies.
Conclusions:
- The meta-analysis quantifies primary and secondary MMR vaccine failure.
- Findings are essential for enhancing mathematical models predicting measles, mumps, and rubella outbreaks.
- Improved predictive modeling can aid public health strategies in highly vaccinated regions.
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