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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Inferring the Ecological Niche of Toxoplasma gondii and Bartonella spp. in Wild Felids
|
|---|---|
| Published in |
Frontiers in Veterinary Science, October 2017
|
| DOI | 10.3389/fvets.2017.00172 |
| Pubmed ID | |
| Authors |
Luis E. Escobar, Scott Carver, Daniel Romero-Alvarez, Sue VandeWoude, Kevin R. Crooks, Michael R. Lappin, Meggan E. Craft |
| Abstract |
Traditional epidemiological studies of disease in animal populations often focus on directly transmitted pathogens. One reason pathogens with complex lifecycles are understudied could be due to challenges associated with detection in vectors and the environment. Ecological niche modeling (ENM) is a methodological approach that overcomes some of the detection challenges often seen with vector or environmentally dependent pathogens. We test this approach using a unique dataset of two pathogens in wild felids across North America: Toxoplasma gondii and Bartonella spp. in bobcats (Lynx rufus) and puma (Puma concolor). We found three main patterns. First, T. gondii showed a broader use of environmental conditions than did Bartonella spp. Also, ecological niche models, and Normalized Difference Vegetation Index satellite imagery, were useful even when applied to wide-ranging hosts. Finally, ENM results from one region could be applied to other regions, thus transferring information across different landscapes. With this research, we detail the uncertainty of epidemiological risk models across novel environments, thereby advancing tools available for epidemiological decision-making. We propose that ENM could be a valuable tool for enabling understanding of transmission risk, contributing to more focused prevention and control options for infectious diseases. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 22% |
| Switzerland | 1 | 11% |
| Unknown | 6 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Science communicators (journalists, bloggers, editors) | 2 | 22% |
| Scientists | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 14% |
| Student > Master | 7 | 14% |
| Student > Ph. D. Student | 6 | 12% |
| Other | 4 | 8% |
| Professor | 3 | 6% |
| Other | 14 | 28% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 32% |
| Veterinary Science and Veterinary Medicine | 9 | 18% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Environmental Science | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 15 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 19 October 2017.
All research outputs
#5,741,042
of 23,005,189 outputs
Outputs from Frontiers in Veterinary Science
#927
of 6,317 outputs
Outputs of similar age
#92,709
of 326,542 outputs
Outputs of similar age from Frontiers in Veterinary Science
#20
of 60 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 6,317 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 85% 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 326,542 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 60 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 66% of its contemporaries.