Evidence map›Paper›PMID 36157183›Full record

ArticleFrontiers in veterinary science2022

Apathogenic proxies for transmission dynamics of a fatal virus.

Marie L J Gilbertson, Nicholas M Fountain-Jones, Jennifer L Malmberg, Roderick B Gagne, Justin S Lee, Simona Kraberger, Sarah Kechejian, Raegan Petch, Elliott S Chiu, Dave Onorato and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in veterinary science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

17 authors.

Marie L J GilbertsonDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Nicholas M Fountain-JonesSchool of Natural Sciences, University of Tasmania, Hobart, TAS, Australia.
Jennifer L MalmbergDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Roderick B GagneDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Justin S LeeDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Simona KrabergerThe Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, United States.
Sarah KechejianDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Raegan PetchDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Elliott S ChiuDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Dave OnoratoFish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, Naples, FL, United States.
Mark W CunninghamFish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, Gainesville, FL, United States.
Kevin R CrooksDepartment of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, United States.
W Chris FunkDepartment of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, United States.
Scott CarverSchool of Natural Sciences, University of Tasmania, Hobart, TAS, Australia.
Sue VandeWoudeDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States.
Kimberly VanderWaalDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Meggan E CraftDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.

Funding

Comparative Medicine and Pathology TrainingT32OD010993 · OD · UNIVERSITY OF MINNESOTA · PI DAVID R BROWN, Cathy S. Carlson · 2012 to 2026
$6.2M
NIH HHS T32 OD010993
6 · The paper itself

Abstract

Identifying drivers of transmission-especially of emerging pathogens-is a formidable challenge for proactive disease management efforts. While close social interactions can be associated with microbial sharing between individuals, and thereby imply dynamics important for transmission, such associations can be obscured by the influences of factors such as shared diets or environments. Directly-transmitted viral agents, specifically those that are rapidly evolving such as many RNA viruses, can allow for high-resolution inference of transmission, and therefore hold promise for elucidating not only which individuals transmit to each other, but also drivers of those transmission events. Here, we tested a novel approach in the Florida panther, which is affected by several directly-transmitted feline retroviruses. We first inferred the transmission network for an apathogenic, directly-transmitted retrovirus, feline immunodeficiency virus (FIV), and then used exponential random graph models to determine drivers structuring this network. We then evaluated the utility of these drivers in predicting transmission of the analogously transmitted, pathogenic agent, feline leukemia virus (FeLV), and compared FIV-based predictions of outbreak dynamics against empirical FeLV outbreak data. FIV transmission was primarily driven by panther age class and distances between panther home range centroids. FIV-based modeling predicted FeLV dynamics similarly to common modeling approaches, but with evidence that FIV-based predictions captured the spatial structuring of the observed FeLV outbreak. While FIV-based predictions of FeLV transmission performed only marginally better than standard approaches, our results highlight the value of proactively identifying drivers of transmission-even based on analogously-transmitted, apathogenic agents-in order to predict transmission of emerging infectious agents. The identification of underlying drivers of transmission, such as through our workflow here, therefore holds promise for improving predictions of pathogen transmission in novel host populations, and could provide new strategies for proactive pathogen management in human and animal systems.

Indexed as

disease modelexponential random graph modelFlorida panthernetwork modelingtransmission heterogeneitytransmission tree

Identifiers

PMID36157183
PMCPMC9493079

What OpenQuestion holds

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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.