Evidence map›Paper›PMID 22476556›Full record

ReviewCurrent topics in microbiology and immunology2012

Animal challenge models of henipavirus infection and pathogenesis.

Thomas W Geisbert, Heinz Feldmann, Christopher C Broder

Open access · greenAbstract readReview
In one paragraph

Review in Current topics in microbiology and immunology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
36.3field-weighted citation impact, top 1% 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

74 citing papers in PubMed, 100 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Nipah virus: a summary for clinicians.International journal of emergency medicine · 2025
    Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Review
  16. Review
  17. Article
  18. Article
  19. AnFrontiers in chemical biology · 2024
    Article
  20. Article

14 more citing papers are in PubMed but not listed here.

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 3 institutions in 1 country.

Thomas W GeisbertGalveston National Laboratory, Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA. tom.geisbert@utmb.edu
Heinz Feldmann
Christopher C Broder
National Institutes of Health · USThe University of Texas Medical Branch at Galveston · USUniformed Services University of the Health Sciences · US

Funding

Viral Hemorrhagic Fevers: Disease Modeling and TransmissionZIAAI001089 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI FELDMANN, HEINRICH · 2009 to 2025
$50.7M
6 · The paper itself

Abstract

The henipaviruses, Hendra virus (HeV), and Nipah virus (NiV), are enigmatic emerging pathogens that causes severe and often fatal neurologic and/or respiratory disease in both animals and humans. Amongst people, case fatality rates range between 40 and 75% and there are no vaccines or treatments approved for human use. A number of species of animals including guinea pigs, hamsters, cats, ferrets, pigs, and African green monkeys have been employed as animal models of human henipavirus infection. Here, we review the development of animal models for henipavirus infection, discuss the pathology and pathogenesis of these models, and assess the utility of each model to recapitulate important aspects of henipavirus-mediated disease seen in humans.

Indexed as

Disease Models, AnimalAnimalsCat DiseasesCatsChiropteraChlorocebus aethiopsCricetinaeFerretsGuinea PigsHendra VirusHenipavirus InfectionsHorsesHost SpecificityHumansNipah VirusSwine

Identifiers

PMID22476556
PMCPMC7120132
OpenAlexW66045189

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.