Evidence map›Paper›PMID 30403733›Full record

ArticlePloS one2018

Transmissibility of emerging viral zoonoses.

Joseph W Walker, Barbara A Han, Isabel M Ott, John M Drake

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
7.1field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Host phylogenetic distance drives trends in virus virulence and transmissibility across the animal-human interface.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Pathogens and planetary change.Nature reviews. Biodiversity · 2025
    Article
  8. Review
  9. Bats host the most virulent-but not the most dangerous-zoonotic viruses.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  10. Article
  11. The science of the host-virus network.Nature microbiology · 2021
    Review
  12. Review
  13. Predictors of zoonotic potential in helminths.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  14. The future of zoonotic risk prediction.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. SARS-CoV-2: What do we know so far?Acta physiologica (Oxford, England) · 2020
    Article
  20. 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 at 2 institutions in 1 country.

Joseph W WalkerOdum School of Ecology, University of Georgia, Athens, Georgia, United States of America.ORCID 0000-0001-6130-8189
Barbara A HanCary Institute for Ecosystem Studies, Millbrook, New York, United States of America.
Isabel M OttSoutheastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, Georgia, United States of America.
John M DrakeOdum School of Ecology, University of Georgia, Athens, Georgia, United States of America.
University of Georgia · USCary Institute of Ecosystem Studies · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective public health research and preparedness requires an accurate understanding of which virus species possess or are at risk of developing human transmissibility. Unfortunately, our ability to identify these viruses is limited by gaps in disease surveillance and an incomplete understanding of the process of viral adaptation. By fitting boosted regression trees to data on 224 human viruses and their associated traits, we developed a model that predicts the human transmission ability of zoonotic viruses with over 84% accuracy. This model identifies several viruses that may have an undocumented capacity for transmission between humans. Viral traits that predicted human transmissibility included infection of nonhuman primates, the absence of a lipid envelope, and detection in the human nervous system and respiratory tract. This predictive model can be used to prioritize high-risk viruses for future research and surveillance, and could inform an integrated early warning system for emerging infectious diseases.

Indexed as

Models, BiologicalAnimalsCommunicable Diseases, EmergingEpidemiological MonitoringHumansMachine LearningPublic HealthVirus DiseasesVirusesZoonoses

Identifiers

PMID30403733
PMCPMC6221319
OpenAlexW2900185100

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.