Evidence map›Paper›PMID 37989240›Full record

ArticleProceedings. Biological sciences2023

Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir.

Rita Ribeiro, Jason Matthiopoulos, Finn Lindgren, Carlos Tello, Carlos M Zariquiey, William Valderrama, Tonie E Rocke, Daniel G Streicker

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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.

Rita RibeiroSchool of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, University Avenue, Graham Kerr Building, Glasgow G12 8QQ, UK.ORCID 0000-0002-9976-3731
Jason MatthiopoulosSchool of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, University Avenue, Graham Kerr Building, Glasgow G12 8QQ, UK.ORCID 0000-0003-3639-8172
Finn LindgrenSchool of Mathematics, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-5833-2011
Carlos TelloILLARIY (Asociación para el Desarrollo y Conservación de los Recursos Naturales), Lima, Perú.
Carlos M ZariquieyILLARIY (Asociación para el Desarrollo y Conservación de los Recursos Naturales), Lima, Perú.
William ValderramaILLARIY (Asociación para el Desarrollo y Conservación de los Recursos Naturales), Lima, Perú.ORCID 0000-0003-4626-1444
Tonie E RockeNational Wildlife Health Center, US Geological Survey, Madison, Wisconsin, USA.ORCID 0000-0003-3933-1563
Daniel G StreickerSchool of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, University Avenue, Graham Kerr Building, Glasgow G12 8QQ, UK.ORCID 0000-0001-7475-2705

Funding

National Science Foundation BBV003798/1National Science Foundation DEB 2011069Wellcome TrustWellcome Trust 217221/Z/19/Z
6 · The paper itself

Abstract

Predicting the spatial occurrence of wildlife is a major challenge for ecology and management. In Latin America, limited knowledge of the number and locations of vampire bat roosts precludes informed allocation of measures intended to prevent rabies spillover to humans and livestock. We inferred the spatial distribution of vampire bat roosts while accounting for observation effort and environmental effects by fitting a log Gaussian Cox process model to the locations of 563 roosts in three regions of Peru. Our model explained 45% of the variance in the observed roost distribution and identified environmental drivers of roost establishment. When correcting for uneven observation effort, our model estimated a total of 2340 roosts, indicating that undetected roosts (76%) exceed known roosts (24%) by threefold. Predicted hotspots of undetected roosts in rabies-free areas revealed high-risk areas for future viral incursions. Using the predicted roost distribution to inform a spatial model of rabies spillover to livestock identified areas with disproportionate underreporting and indicated a higher rabies burden than previously recognized. We provide a transferrable approach to infer the distribution of a mostly unobserved bat reservoir that can inform strategies to prevent the re-emergence of an important zoonosis.

Indexed as

ChiropteraRabiesRabies virusAnimalsHumansLatin AmericaLivestockZoonosesdetection probabilityGaussian random fieldpartially observed speciesspecies distribution modelsvampire bat rabies

Identifiers

PMID37989240
PMCPMC10688441

What OpenQuestion holds

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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.