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Predictive spatial risk model of poliovirus to aid prioritization and hasten eradication in Nigeria

Overview of attention for article published in BMC Medicine, June 2014
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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 (90th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
9 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
72 Mendeley
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Title
Predictive spatial risk model of poliovirus to aid prioritization and hasten eradication in Nigeria
Published in
BMC Medicine, June 2014
DOI 10.1186/1741-7015-12-92
Pubmed ID
Authors

Alexander M Upfill-Brown, Hil M Lyons, Muhammad A Pate, Faisal Shuaib, Shahzad Baig, Hao Hu, Philip A Eckhoff, Guillaume Chabot-Couture

Abstract

One of the challenges facing the Global Polio Eradication Initiative is efficiently directing limited resources, such as specially trained personnel, community outreach activities, and satellite vaccinator tracking, to the most at-risk areas to maximize the impact of interventions. A validated predictive model of wild poliovirus circulation would greatly inform prioritization efforts by accurately forecasting areas at greatest risk, thus enabling the greatest effect of program interventions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
United States 2 3%
Angola 1 1%
Brazil 1 1%
Unknown 66 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 33%
Student > Ph. D. Student 14 19%
Student > Master 11 15%
Student > Bachelor 3 4%
Other 3 4%
Other 6 8%
Unknown 11 15%
Readers by discipline Count As %
Medicine and Dentistry 16 22%
Agricultural and Biological Sciences 12 17%
Mathematics 6 8%
Social Sciences 4 6%
Nursing and Health Professions 3 4%
Other 19 26%
Unknown 12 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 03 October 2022.
All research outputs
#2,060,510
of 23,466,057 outputs
Outputs from BMC Medicine
#1,379
of 3,536 outputs
Outputs of similar age
#21,475
of 229,770 outputs
Outputs of similar age from BMC Medicine
#30
of 57 outputs
Altmetric has tracked 23,466,057 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,536 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.7. This one has gotten more attention than average, scoring higher than 61% 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 229,770 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.