Evidence map›Paper›PMID 29090215›Full record

ArticleFrontiers in veterinary science2017

Inferring the Ecological Niche of

Luis E Escobar, Scott Carver, Daniel Romero-Alvarez, Sue VandeWoude, Kevin R Crooks, Michael R Lappin, Meggan E Craft

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 39% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 24 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 2 countries.

Luis E EscobarDepartment of Veterinary Population Medicine, University of Minnesota, Minneapolis, MN, United States.
Scott CarverSchool of Biological Sciences, University of Tasmania, Hobart, TAS, Australia.
Daniel Romero-AlvarezDepartment of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS, United States.
Sue VandeWoudeDepartment of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States.
Kevin R CrooksDepartment of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, United States.
Michael R LappinDepartment of Clinical Sciences, Colorado State University, Fort Collins, CO, United States.
Meggan E CraftDepartment of Veterinary Population Medicine, University of Minnesota, Minneapolis, MN, United States.
Colorado State University · USUniversity of Kansas · USUniversity of Minnesota · USUniversity of Tasmania · AUVirginia Tech · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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:

Indexed as

Bartonella spp.environmental transmissionLynx rufusnichePuma concolorToxoplasma gondii

Identifiers

PMID29090215
PMCPMC5650989
OpenAlexW2767114827

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.