Evidence map›Paper›PMID 36877838›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Inferring the disruption of rabies circulation in vampire bat populations using a betaherpesvirus-vectored transmissible vaccine.

Megan E Griffiths, Diana K Meza, Daniel T Haydon, Daniel G Streicker

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

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  17. Inferring the disruption of rabies circulation in vampire bat populations using a betaherpesvirus-vectored transmissible vaccine.Proceedings of the National Academy of Sciences of the United States of America · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Megan E GriffithsMedical Research Council-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, United Kingdom.
Diana K MezaSchool of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow G61 1QH, United Kingdom.
Daniel T HaydonSchool of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow G61 1QH, United Kingdom.ORCID 0000-0002-1240-1886
Daniel G StreickerMedical Research Council-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, United Kingdom.ORCID 0000-0001-7475-2705
MRC University of Glasgow Centre for Virus Research · GBUniversity of Glasgow · GB

Funding

Medical Research Council MC_UU_00034/3Medical Research Council MC_UU_12014/12Medical Research Council MC_UU_12014/8Wellcome Trust
6 · The paper itself

Abstract

Transmissible vaccines are an emerging biotechnology that hold prospects to eliminate pathogens from wildlife populations. Such vaccines would genetically modify naturally occurring, nonpathogenic viruses ("viral vectors") to express pathogen antigens while retaining their capacity to transmit. The epidemiology of candidate viral vectors within the target wildlife population has been notoriously challenging to resolve but underpins the selection of effective vectors prior to major investments in vaccine development. Here, we used spatiotemporally replicated deep sequencing to parameterize competing epidemiological mechanistic models of

Indexed as

BetaherpesvirinaeChiropteraRabiesRabies VaccinesAnimalsAnimals, WildHumansVaccinationRabies VaccinesDesmodus rotundusepidemiological modellyssaviruswildlife vaccinationzoonoses

Identifiers

PMID36877838
PMCPMC10089182
OpenAlexW4323306395

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.