Evidence map›Paper›PMID 40303736›Full record

ArticleTransboundary and emerging diseases2023

Quantifying Spillover Risk with an Integrated Bat-Rabies Dynamic Modeling Framework.

Eva Janoušková, Jennifer Rokhsar, Manuel Jara, Mahbod Entezami, Daniel L Horton, Ricardo Augusto Dias, Gustavo Machado, Joaquín M Prada

Abstract read
In one paragraph

Article in Transboundary and emerging diseases, 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

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

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

8 authors.

Eva JanouškováSchool of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID https://orcid.org/0000-0002-4104-0119
Jennifer RokhsarSchool of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID https://orcid.org/0000-0001-7729-8288
Manuel JaraDepartment of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA.ORCID https://orcid.org/0000-0001-7011-6218
Mahbod EntezamiSchool of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID https://orcid.org/0000-0003-1854-3209
Daniel L HortonSchool of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID https://orcid.org/0000-0002-9126-2756
Ricardo Augusto DiasDepartment of Preventive Veterinary Medicine and Animal Health, School of Veterinary Medicine, University of Sao Paulo, Sao Paulo, Brazil.ORCID https://orcid.org/0000-0002-8241-7699
Gustavo MachadoDepartment of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA.ORCID https://orcid.org/0000-0001-7552-6144
Joaquín M PradaSchool of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID https://orcid.org/0000-0003-4699-5931

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vampire bat-transmitted rabies has recently become the leading cause of rabies mortality in both humans and livestock in Latin America. Evaluating risk of transmission from bats to other animal species has thus become a priority in the region. An integrated bat-rabies dynamic modeling framework quantifying spillover risk to cattle farms was developed. The model is spatially explicit and is calibrated to the state of São Paulo, using real roost and farm locations. Roost and farm characteristics, as well as environmental data through an ecological niche model, are used to modulate rabies transmission. Interventions aimed at reducing risk in roosts (such as bat culling or vaccination) and in farms (cattle vaccination) were considered as control strategies. Both interventions significantly reduce the number of outbreaks in farms and disease spread (based on distance from source), with control in roosts being a significantly better intervention. High-risk areas were also identified, which can support ongoing programs, leading to more effective control interventions.

Indexed as

Cattle DiseasesChiropteraRabiesAnimalsBrazilCattleModels, Biological

Identifiers

PMID40303736
PMCPMC12017007

What OpenQuestion holds

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LicenceCC BY
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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.