Evidence map›Paper›PMID 37980452›Full record

ArticleScientific reports2023

Range area and the fast-slow continuum of life history traits predict pathogen richness in wild mammals.

Jacqueline Choo, Le T P Nghiem, Ana Benítez-López, Luis R Carrasco

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Jacqueline ChooDepartment of Biological Sciences, National University of Singapore, Singapore, Singapore. jacqueline.choo@u.nus.edu.
Le T P NghiemUniversity of British Columbia, Vancouver, Canada.
Ana Benítez-LópezDepartment of Biogeography and Global Change, Museo Nacional de Ciencias Naturales (MNCN-CSIC), Madrid, Spain. ana.benitez@mncn.csic.es.
Luis R CarrascoDepartment of Biological Sciences, National University of Singapore, Singapore, Singapore.

Funding

Ministry of Education - Singapore Tier 1 grant A-0004770-00-00Ramón y Cajal grant RYC2021-031737-I
6 · The paper itself

Abstract

Surveillance of pathogen richness in wildlife is needed to identify host species with a high risk of zoonotic disease spillover. While several predictors of pathogen richness in wildlife hosts have been proposed, their relative importance has not been formally examined. This hampers our ability to identify potential disease reservoirs, particularly in remote areas with limited surveillance efforts. Here we analyzed 14 proposed predictors of pathogen richness using ensemble modeling and a dataset of 1040 host species to identify the most important predictors of pathogen richness in wild mammal species. After controlling for research effort, larger species geographic range area was identified to be associated with higher pathogen richness. We found evidence of duality in the relationship between the fast-slow continuum of life-history traits and pathogen richness, where pathogen richness increases near the extremities. Taxonomic orders Carnivora, Proboscidea, Artiodactyla, and Perissodactyla were predicted to host high pathogen richness. The top three species with the highest pathogen richness predicted by our ensemble model were Canis lupus, Sus scrofa, and Alces alces. Our results can help support evidence-informed pathogen surveillance and disease reservoir management to prevent the emergence of future zoonotic diseases.

Indexed as

CarnivoraDeerLife History TraitsAnimalsAnimals, WildDisease ReservoirsMammalsZoonoses

Identifiers

PMID37980452
PMCPMC10657380

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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.