↓ Skip to main content

Effects of georeferencing effort on mapping monkeypox case distributions and transmission risk

Overview of attention for article published in International Journal of Health Geographics, January 2012
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter
facebook
2 Facebook pages

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
142 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
Effects of georeferencing effort on mapping monkeypox case distributions and transmission risk
Published in
International Journal of Health Geographics, January 2012
DOI 10.1186/1476-072x-11-23
Pubmed ID
Authors

R Lash, Darin S Carroll, Christine M Hughes, Yoshinori Nakazawa, Kevin Karem, Inger K Damon, A Peterson

Abstract

Maps of disease occurrences and GIS-based models of disease transmission risk are increasingly common, and both rely on georeferenced diseases data. Automated methods for georeferencing disease data have been widely studied for developed countries with rich sources of geographic referenced data. However, the transferability of these methods to countries without comparable geographic reference data, particularly when working with historical disease data, has not been as widely studied. Historically, precise geographic information about where individual cases occur has been collected and stored verbally, identifying specific locations using place names. Georeferencing historic data is challenging however, because it is difficult to find appropriate geographic reference data to match the place names to. Here, we assess the degree of care and research invested in converting textual descriptions of disease occurrence locations to numerical grid coordinates (latitude and longitude). Specifically, we develop three datasets from the same, original monkeypox disease occurrence data, with varying levels of care and effort: the first based on an automated web-service, the second improving on the first by reference to additional maps and digital gazetteers, and the third improving still more based on extensive consultation of legacy surveillance records that provided considerable additional information about each case. To illustrate the implications of these seemingly subtle improvements in data quality, we develop ecological niche models and predictive maps of monkeypox transmission risk based on each of the three occurrence data sets.

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 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Brazil 2 1%
Italy 1 <1%
Canada 1 <1%
India 1 <1%
Spain 1 <1%
Denmark 1 <1%
Unknown 131 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 20%
Student > Master 24 17%
Student > Ph. D. Student 22 15%
Student > Bachelor 12 8%
Student > Doctoral Student 11 8%
Other 33 23%
Unknown 11 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 25%
Medicine and Dentistry 27 19%
Environmental Science 13 9%
Social Sciences 9 6%
Computer Science 6 4%
Other 31 22%
Unknown 21 15%

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 12 July 2012.
All research outputs
#13,322,012
of 21,334,388 outputs
Outputs from International Journal of Health Geographics
#400
of 619 outputs
Outputs of similar age
#82,353
of 142,337 outputs
Outputs of similar age from International Journal of Health Geographics
#1
of 1 outputs
Altmetric has tracked 21,334,388 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 619 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one is in the 33rd percentile – i.e., 33% 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 142,337 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them