↓ Skip to main content

Modelling the risk of transfusion transmission from travelling donors

Overview of attention for article published in BMC Infectious Diseases, April 2016
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
49 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Modelling the risk of transfusion transmission from travelling donors
Published in
BMC Infectious Diseases, April 2016
DOI 10.1186/s12879-016-1452-z
Pubmed ID
Authors

Tonderai Mapako, Welling Oei, Marinus van Hulst, Mirjam E. Kretzschmar, Mart P. Janssen

Abstract

The EUFRAT (European Up-Front Risk Assessment Tool) was developed as an online risk assessment tool ( http://eufrattool.ecdc.europa.eu ) to help decision-makers assess the transmission risk of emerging infectious diseases (EID) through blood transfusion. The aim of this study is to extend the methodology developed in the EUFRAT project to quantify the transfusion transmission (TT) risk from travelling donors. A generic model for estimating the TT risk from a group of travelling donors that visited an EID risk area was developed. In addition, the new model distinguishes projected future transmissions from those that have already occurred. As an illustration the model was applied to the outbreaks of chikungunya in Italy in 2007 and Q fever in the Netherlands in 2007-2009. Formulas for calculating the travelling donors' TT risk were derived. For the chikungunya outbreak in Italy an early intervention (at the end of week 7 after the start of the outbreak, so after only 19 % of all cases) would have been required to prevent only 41 % of all expected transmissions at that time. For Q fever, in which the transmission of chronic Q fever is considered, even at the end of the third annual outbreak's peak 47 % of all (chronic) Q fever transmissions could still be prevented. The updated model allows estimation of the infection transmission risk from travelling donors. In combination with the distinction between past and future transmissions, these estimates provide valuable information to support decisions concerning communication with the public and/or the implementation of safety interventions.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
United States 1 2%
Unknown 47 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 24%
Student > Master 9 18%
Other 4 8%
Student > Ph. D. Student 4 8%
Student > Postgraduate 3 6%
Other 6 12%
Unknown 11 22%
Readers by discipline Count As %
Medicine and Dentistry 10 20%
Agricultural and Biological Sciences 8 16%
Nursing and Health Professions 5 10%
Biochemistry, Genetics and Molecular Biology 3 6%
Social Sciences 2 4%
Other 10 20%
Unknown 11 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 31 October 2016.
All research outputs
#4,791,355
of 9,726,436 outputs
Outputs from BMC Infectious Diseases
#1,768
of 4,136 outputs
Outputs of similar age
#125,438
of 282,013 outputs
Outputs of similar age from BMC Infectious Diseases
#52
of 97 outputs
Altmetric has tracked 9,726,436 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,136 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 54% 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 282,013 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.