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EURISWEB – Web-based epidemiological surveillance of antibiotic-resistant pneumococci in Day Care Centers

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2003
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Mentioned by

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2 tweeters

Citations

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11 Dimensions

Readers on

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7 Mendeley
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Title
EURISWEB – Web-based epidemiological surveillance of antibiotic-resistant pneumococci in Day Care Centers
Published in
BMC Medical Informatics and Decision Making, July 2003
DOI 10.1186/1472-6947-3-9
Pubmed ID
Authors

Sara Silva, Rodrigo Gouveia-Oliveira, António Maretzek, João Carriço, Thorolfur Gudnason, Karl G Kristinsson, Karl Ekdahl, António Brito-Avô, Alexander Tomasz, Ilda Santos Sanches, Hermínia de Lencastre, Jonas Almeida

Abstract

EURIS (European Resistance Intervention Study) was launched as a multinational study in September of 2000 to identify the multitude of complex risk factors that contribute to the high carriage rate of drug resistant Streptococcus pneumoniae strains in children attending Day Care Centers in several European countries. Access to the very large number of data required the development of a web-based infrastructure - EURISWEB - that includes a relational online database, coupled with a query system for data retrieval, and allows integrative storage of demographic, clinical and molecular biology data generated in EURIS. All components of the system were developed using open source programming tools: data storage management was supported by PostgreSQL, and the hypertext preprocessor to generate the web pages was implemented using PHP. The query system is based on a software agent running in the background specifically developed for EURIS. The website currently contains data related to 13,500 nasopharyngeal samples and over one million measures taken from 5,250 individual children, as well as over one thousand pre-made and user-made queries aggregated into several reports, approximately. It is presently in use by participating researchers from three countries (Iceland, Portugal and Sweden). An operational model centered on a PHP engine builds the interface between the user and the database automatically, allowing an easy maintenance of the system. The query system is also sufficiently adaptable to allow the integration of several advanced data analysis procedures far more demanding than simple queries, eventually including artificial intelligence predictive models.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Faroe Islands 1 14%
Unknown 6 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 43%
Student > Doctoral Student 2 29%
Lecturer 1 14%
Student > Master 1 14%
Readers by discipline Count As %
Medicine and Dentistry 2 29%
Computer Science 1 14%
Agricultural and Biological Sciences 1 14%
Immunology and Microbiology 1 14%
Earth and Planetary Sciences 1 14%
Other 1 14%

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 23 August 2014.
All research outputs
#7,784,730
of 12,409,138 outputs
Outputs from BMC Medical Informatics and Decision Making
#782
of 1,122 outputs
Outputs of similar age
#77,435
of 143,367 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 6 outputs
Altmetric has tracked 12,409,138 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,122 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 20th percentile – i.e., 20% 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 143,367 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.