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Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases

Overview of attention for article published in PLoS Neglected Tropical Diseases, December 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

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12 X users
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1 Facebook page

Citations

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39 Dimensions

Readers on

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136 Mendeley
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Title
Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases
Published in
PLoS Neglected Tropical Diseases, December 2015
DOI 10.1371/journal.pntd.0004164
Pubmed ID
Authors

Nicholas A. S. Hamm, Ricardo J. Soares Magalhães, Archie C. A. Clements

Abstract

Earth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial data quality (SDQ), which limit the utilization of EO and pose challenges for its more effective use. We searched Web of Science and PubMed for studies related to EO and echinococossis, leptospirosis, schistosomiasis, and soil-transmitted helminth infections. Relevant literature was also identified from the bibliographies of those papers. We found that extensive use is made of EO products in the study of NTD epidemiology; however, the quality of these products is usually given little explicit attention. We review key issues in SDQ concerning spatial and temporal scale, uncertainty, and the documentation and use of quality information. We give examples of how these issues may interact with uncertainty in NTD data to affect the output of an epidemiological analysis. We conclude that researchers should give careful attention to SDQ when designing NTD spatial-epidemiological studies. This should be used to inform uncertainty analysis in the epidemiological study. SDQ should be documented and made available to other researchers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Colombia 1 <1%
Brazil 1 <1%
Unknown 133 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 18%
Researcher 17 13%
Student > Ph. D. Student 14 10%
Student > Bachelor 12 9%
Student > Doctoral Student 8 6%
Other 26 19%
Unknown 34 25%
Readers by discipline Count As %
Medicine and Dentistry 17 13%
Agricultural and Biological Sciences 14 10%
Environmental Science 12 9%
Earth and Planetary Sciences 10 7%
Veterinary Science and Veterinary Medicine 8 6%
Other 39 29%
Unknown 36 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 05 January 2016.
All research outputs
#5,211,314
of 25,374,917 outputs
Outputs from PLoS Neglected Tropical Diseases
#3,254
of 9,377 outputs
Outputs of similar age
#77,162
of 380,103 outputs
Outputs of similar age from PLoS Neglected Tropical Diseases
#54
of 189 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,377 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 65% 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 380,103 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.