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Direct and indirect effects of influenza vaccination

Overview of attention for article published in BMC Infectious Diseases, April 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)

Mentioned by

news
1 news outlet
twitter
8 tweeters

Citations

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46 Dimensions

Readers on

mendeley
71 Mendeley
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Title
Direct and indirect effects of influenza vaccination
Published in
BMC Infectious Diseases, April 2017
DOI 10.1186/s12879-017-2399-4
Pubmed ID
Authors

Martin Eichner, Markus Schwehm, Linda Eichner, Laetitia Gerlier

Abstract

After vaccination, vaccinees acquire some protection against infection and/or disease. Vaccination, therefore, reduces the number of infections in the population. Due to this herd protection, not everybody needs to be vaccinated to prevent infections from spreading. We quantify direct and indirect effects of influenza vaccination examining the standard Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Recovered-Susceptible (SIRS) model as well as simulation results of a sophisticated simulation tool which allows for seasonal transmission of four influenza strains in a population with realistic demography and age-dependent contact patterns. As shown analytically for the simple SIR and SIRS transmission models, indirect vaccination effects are bigger than direct ones if the effective reproduction number of disease transmission is close to the critical value of 1. Simulation results for 20-60% vaccination with live influenza vaccine of 2-17 year old children in Germany, averaged over 10 years (2017-26), confirm this result: four to seven times as many influenza cases are prevented among non-vaccinated individuals as among vaccinees. For complications like death due to influenza which occur much more frequently in the unvaccinated elderly than in the vaccination target group of children, indirect benefits can surpass direct ones by a factor of 20 or even more than 30. The true effect of vaccination can be much bigger than what would be expected by only looking at vaccination coverage and vaccine efficacy.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 15%
Student > Master 10 14%
Researcher 8 11%
Student > Postgraduate 8 11%
Other 6 8%
Other 8 11%
Unknown 20 28%
Readers by discipline Count As %
Medicine and Dentistry 19 27%
Biochemistry, Genetics and Molecular Biology 6 8%
Nursing and Health Professions 4 6%
Economics, Econometrics and Finance 3 4%
Agricultural and Biological Sciences 2 3%
Other 12 17%
Unknown 25 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 22 November 2021.
All research outputs
#2,147,145
of 22,530,935 outputs
Outputs from BMC Infectious Diseases
#606
of 7,592 outputs
Outputs of similar age
#40,390
of 285,320 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 1 outputs
Altmetric has tracked 22,530,935 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 7,592 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has done particularly well, scoring higher than 91% of its peers.
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 285,320 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 85% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them