↓ Skip to main content

FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations

Overview of attention for article published in BMC Public Health, October 2013
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
59 news outlets
blogs
2 blogs
twitter
14 X users
googleplus
1 Google+ user

Citations

dimensions_citation
170 Dimensions

Readers on

mendeley
228 Mendeley
citeulike
1 CiteULike
Title
FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
Published in
BMC Public Health, October 2013
DOI 10.1186/1471-2458-13-940
Pubmed ID
Authors

John J Grefenstette, Shawn T Brown, Roni Rosenfeld, Jay DePasse, Nathan TB Stone, Phillip C Cooley, William D Wheaton, Alona Fyshe, David D Galloway, Anuroop Sriram, Hasan Guclu, Thomas Abraham, Donald S Burke

Abstract

Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 228 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 4%
Israel 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Canada 1 <1%
China 1 <1%
Denmark 1 <1%
Unknown 213 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 21%
Student > Ph. D. Student 31 14%
Student > Master 25 11%
Professor > Associate Professor 16 7%
Professor 15 7%
Other 53 23%
Unknown 41 18%
Readers by discipline Count As %
Computer Science 33 14%
Medicine and Dentistry 29 13%
Social Sciences 15 7%
Agricultural and Biological Sciences 13 6%
Engineering 11 5%
Other 67 29%
Unknown 60 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 461. 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 09 January 2023.
All research outputs
#54,661
of 24,280,456 outputs
Outputs from BMC Public Health
#56
of 16,006 outputs
Outputs of similar age
#319
of 214,551 outputs
Outputs of similar age from BMC Public Health
#2
of 284 outputs
Altmetric has tracked 24,280,456 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,006 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has done particularly well, scoring higher than 99% 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 214,551 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 99% of its contemporaries.
We're also able to compare this research output to 284 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.