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Influence of the pneumococcal conjugate vaccines on the temporal variation of pneumococcal carriage and the nasal microbiota in healthy infants: a longitudinal analysis of a case–control study

Overview of attention for article published in Microbiome, July 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog
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15 X users

Citations

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32 Dimensions

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Title
Influence of the pneumococcal conjugate vaccines on the temporal variation of pneumococcal carriage and the nasal microbiota in healthy infants: a longitudinal analysis of a case–control study
Published in
Microbiome, July 2017
DOI 10.1186/s40168-017-0302-6
Pubmed ID
Authors

Moana Mika, Josua Maurer, Insa Korten, Aurélie Allemann, Suzanne Aebi, Silvio D. Brugger, Weihong Qi, Urs Frey, Philipp Latzin, Markus Hilty

Abstract

Bacterial colonization of the upper airways is a prerequisite for subsequent invasive disease. With the introduction of the 7- and 13-valent pneumococcal conjugate vaccines (PCV7 and PCV13), changes in pneumococcal upper airway colonization have been described. It is, however, less evident whether the vaccines lead to compositional changes of the upper airway microbiota. Here, we performed a case-control study using samples from a longitudinal infant cohort from Switzerland. We compared pneumococcal carriage and the nasal microbiota within the first year of life of healthy infants vaccinated with either PCV7 (n = 20, born in 2010) or PCV13 (n = 21, born between 2011 and 2013). Nasal swabs were collected every second week (n = 763 in total). Pneumococcal carriage was analyzed by quantitative PCR of the pneumococcal-specific lytA gene. Analysis of the bacterial core microbiota was performed based on 16S rRNA sequencing and subsequent oligotyping. We exclusively performed oligotyping of the core microbiota members, which were defined as the five most abundant bacterial families (Moraxellaceae, Streptococcaceae, Staphylococcaceae, Corynebacteriaceae, and Pasteurellaceae). Linear mixed effect (LME) and negative binomial regression models were used for statistical analyses. We found a higher number of samples positive for pneumococcal carriage in PCV7- compared to PCV13-vaccinated infants (LME model; P = 0.01). In contrast, infants vaccinated in the PCV13 era had an increased alpha diversity as measured by the richness and the Shannon Diversity Index (LME model; P = 0.003 and P = 0.01, respectively). Accordingly, the PCV13 era was associated with clusters of a higher diversity than PCV7-associated clusters. Furthermore, infants vaccinated with PCV13 had a higher binary-based within-subject microbiota similarity, as well as a decreased Jensen-Shannon distance over time as compared to PCV7-vaccinated infants, indicating a higher microbiota stability in the PCV13 era (LME model and t test; P = 0.06 and P = 0.03, respectively). We hypothesize that the higher diversity and stability of the upper airway microbiota in the PCV13 era is the result of the lower pneumococcal carriage rate. This seems to indicate that the nasal bacterial microbiota of infants has changed in recent years as compared to the beginning of this study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 23%
Student > Bachelor 8 13%
Student > Ph. D. Student 8 13%
Student > Master 8 13%
Student > Postgraduate 4 6%
Other 8 13%
Unknown 12 19%
Readers by discipline Count As %
Medicine and Dentistry 17 27%
Biochemistry, Genetics and Molecular Biology 9 15%
Agricultural and Biological Sciences 9 15%
Immunology and Microbiology 7 11%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 5 8%
Unknown 13 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 August 2018.
All research outputs
#2,520,974
of 25,711,518 outputs
Outputs from Microbiome
#993
of 1,790 outputs
Outputs of similar age
#45,533
of 327,490 outputs
Outputs of similar age from Microbiome
#37
of 56 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,790 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.9. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,490 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.