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The representativeness of a European multi-center network for influenza-like-illness participatory surveillance

Overview of attention for article published in BMC Public Health, September 2014
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Mentioned by

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1 tweeter
facebook
1 Facebook page

Citations

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41 Dimensions

Readers on

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84 Mendeley
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Title
The representativeness of a European multi-center network for influenza-like-illness participatory surveillance
Published in
BMC Public Health, September 2014
DOI 10.1186/1471-2458-14-984
Pubmed ID
25240865
Authors

Pietro Cantarelli, Marion Debin, Clément Turbelin, Chiara Poletto, Thierry Blanchon, Alessandra Falchi, Thomas Hanslik, Isabelle Bonmarin, Daniel Levy-Bruhl, Alessandra Micheletti, Daniela Paolotti, Alessandro Vespignani, John Edmunds, Ken Eames, Ronald Smallenburg, Carl Koppeschaar, Ana O Franco, Vitor Faustino, AnnaSara Carnahan, Moa Rehn, Vittoria Colizza

Abstract

The Internet is becoming more commonly used as a tool for disease surveillance. Similarly to other surveillance systems and to studies using online data collection, Internet-based surveillance will have biases in participation, affecting the generalizability of the results. Here we quantify the participation biases of Influenzanet, an ongoing European-wide network of Internet-based participatory surveillance systems for influenza-like-illness.

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Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Vietnam 1 1%
Unknown 82 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 26%
Student > Ph. D. Student 13 15%
Researcher 6 7%
Student > Doctoral Student 5 6%
Professor > Associate Professor 4 5%
Other 17 20%
Unknown 17 20%
Readers by discipline Count As %
Medicine and Dentistry 22 26%
Nursing and Health Professions 9 11%
Social Sciences 8 10%
Agricultural and Biological Sciences 7 8%
Mathematics 5 6%
Other 15 18%
Unknown 18 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 December 2014.
All research outputs
#17,728,987
of 22,768,097 outputs
Outputs from BMC Public Health
#12,432
of 14,840 outputs
Outputs of similar age
#168,370
of 250,566 outputs
Outputs of similar age from BMC Public Health
#240
of 279 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,840 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 13th percentile – i.e., 13% 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 250,566 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 279 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.

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