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Statistical air quality predictions for public health surveillance: evaluation and generation of county level metrics of PM2.5 for the environmental public health tracking network

Overview of attention for article published in International Journal of Health Geographics, January 2013
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1 Facebook page

Citations

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32 Mendeley
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Title
Statistical air quality predictions for public health surveillance: evaluation and generation of county level metrics of PM2.5 for the environmental public health tracking network
Published in
International Journal of Health Geographics, January 2013
DOI 10.1186/1476-072x-12-12
Pubmed ID
Authors

Ambarish Vaidyanathan, William Dimmick, Scott R Kegler, Judith R Qualters

Abstract

The Centers for Disease Control and Prevention (CDC) developed county level metrics for the Environmental Public Health Tracking Network (Tracking Network) to characterize potential population exposure to airborne particles with an aerodynamic diameter of 2.5 μm or less (PM(2.5)). These metrics are based on Federal Reference Method (FRM) air monitor data in the Environmental Protection Agency (EPA) Air Quality System (AQS); however, monitor data are limited in space and time. In order to understand air quality in all areas and on days without monitor data, the CDC collaborated with the EPA in the development of hierarchical Bayesian (HB) based predictions of PM(2.5) concentrations. This paper describes the generation and evaluation of HB-based county level estimates of PM(2.5).

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Malaysia 1 3%
United Kingdom 1 3%
Canada 1 3%
Unknown 27 84%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 25%
Researcher 7 22%
Other 5 16%
Student > Ph. D. Student 5 16%
Student > Postgraduate 2 6%
Other 3 9%
Unknown 2 6%
Readers by discipline Count As %
Environmental Science 10 31%
Medicine and Dentistry 5 16%
Social Sciences 4 13%
Earth and Planetary Sciences 2 6%
Engineering 2 6%
Other 5 16%
Unknown 4 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 14 March 2013.
All research outputs
#11,160,852
of 12,545,316 outputs
Outputs from International Journal of Health Geographics
#400
of 475 outputs
Outputs of similar age
#120,516
of 143,471 outputs
Outputs of similar age from International Journal of Health Geographics
#6
of 7 outputs
Altmetric has tracked 12,545,316 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 1st percentile – i.e., 1% 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 143,471 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.