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X Demographics
Mendeley readers
Attention Score in Context
Title |
An approximation of herd effect due to vaccinating children against seasonal influenza – a potential solution to the incorporation of indirect effects into static models
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Published in |
BMC Infectious Diseases, January 2013
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DOI | 10.1186/1471-2334-13-25 |
Pubmed ID | |
Authors |
Ilse Van Vlaenderen, Laure-Anne Van Bellinghen, Genevieve Meier, Barbara Poulsen Nautrup |
Abstract |
Indirect herd effect from vaccination of children offers potential for improving the effectiveness of influenza prevention in the remaining unvaccinated population. Static models used in cost-effectiveness analyses cannot dynamically capture herd effects. The objective of this study was to develop a methodology to allow herd effect associated with vaccinating children against seasonal influenza to be incorporated into static models evaluating the cost-effectiveness of influenza vaccination. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 20% |
Unknown | 4 | 80% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Scientists | 1 | 20% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 2% |
Germany | 1 | 2% |
Unknown | 50 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 21% |
Researcher | 11 | 21% |
Student > Master | 9 | 17% |
Student > Bachelor | 5 | 10% |
Professor > Associate Professor | 3 | 6% |
Other | 7 | 13% |
Unknown | 6 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 17 | 33% |
Nursing and Health Professions | 6 | 12% |
Biochemistry, Genetics and Molecular Biology | 3 | 6% |
Agricultural and Biological Sciences | 3 | 6% |
Business, Management and Accounting | 2 | 4% |
Other | 11 | 21% |
Unknown | 10 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 19 June 2013.
All research outputs
#13,028,542
of 22,693,205 outputs
Outputs from BMC Infectious Diseases
#3,096
of 7,644 outputs
Outputs of similar age
#152,327
of 279,188 outputs
Outputs of similar age from BMC Infectious Diseases
#59
of 175 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,644 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 58% 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 279,188 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 175 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.