Evidence map›Paper›PMID 28470362›Full record

ArticleEcoHealth2017

Pathogen Exposure in Cattle at the Livestock-Wildlife Interface.

Malavika Rajeev, Mathew Mutinda, Vanessa O Ezenwa

Abstract read
PubMed Publisher
In one paragraph

Article in EcoHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
1.8field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 23 citations in OpenAlex.

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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

3 authors at 2 institutions in 2 countries.

Malavika RajeevOdum School of Ecology, University of Georgia, Athens, GA, 30602-2202, USA.
Mathew MutindaKenya Wildlife Service, Nairobi, Kenya.
Vanessa O EzenwaOdum School of Ecology, University of Georgia, Athens, GA, 30602-2202, USA. vezenwa@uga.edu.ORCID 0000-0002-8078-1913
University of Georgia · USKenya Wildlife Service · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Land use is an important driver of variation in human infectious disease risk, but less is known about how land use affects disease risk in livestock. To understand how land use is associated with disease risk in livestock, we examined patterns of pathogen exposure in cattle across two livestock ranching systems in rural Kenya: private ranches with low- to medium-intensity cattle production and high wildlife densities, and group ranches with high-intensity cattle production and low wildlife densities. We surveyed cattle from six ranches for three pathogens: Brucella spp., bovine viral diarrhea virus (BVDV) and Leptospira serovar Hardjo. We found that exposure risk for Leptospira was higher on private ranches than on group ranches, but there was no difference in exposure by ranch type for Brucella or BVDV. We hypothesize that variation in livestock and wildlife contact patterns between ranch types may be driving the pattern observed for Leptospira exposure and that the different relationships we found between exposure risk and ranch type by pathogen may be explained by differences in transmission mode. Overall, our results suggest that wildlife-livestock contact patterns may play a key role in shaping pathogen transmission to livestock and that the magnitude of such effects likely depend on characteristics of the pathogen in question.

Indexed as

AnimalsAnimals, WildBrucellaBrucellosisCattleCattle DiseasesDiarrhea Viruses, Bovine ViralKenyaLeptospiraLivestockRisk FactorsBovine viral diarrhea virusBrucellaLeptospiraPastoralistRanching

Identifiers

PMID28470362
OpenAlexW2610458905

What OpenQuestion holds

Textmetadata
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.