Evidence map›Paper›PMID 32054908›Full record

ArticleScientific reports2020

Waterfowl occurrence and residence time as indicators of H5 and H7 avian influenza in North American Poultry.

John M Humphreys, Andrew M Ramey, David C Douglas, Jennifer M Mullinax, Catherine Soos, Paul Link, Patrick Walther, Diann J Prosser

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

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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 at 5 institutions in 2 countries.

John M HumphreysMichigan State University, East Lansing, Michigan, USA. jmh09r@my.fsu.edu.ORCID http://orcid.org/0000-0002-8464-0886
Andrew M RameyU.S. Geological Survey, Alaska Science Center, Anchorage, Alaska, USA.
David C DouglasU.S. Geological Survey, Alaska Science Center, Anchorage, Alaska, USA.ORCID http://orcid.org/0000-0003-0186-1104
Jennifer M MullinaxUniversity of Maryland, College Park, Maryland, USA.
Catherine SoosEnvironment and Climate Change Canada, Ecotoxicology and Wildlife Health Division, Saskatchewan, Canada.ORCID http://orcid.org/0000-0003-4610-3614
Paul LinkLouisiana Department of Wildlife and Fisheries, Baton Rouge, Louisiana, USA.
Patrick WaltherU.S. Fish and Wildlife Service, Texas Chenier Plain Refuge Complex, Anahuac, Texas, USA.
Diann J ProsserU.S. Geological Survey, Patuxent Wildlife Research Center, Laurel, Maryland, USA.
United States Geological Survey · USEnvironment and Climate Change Canada · CALouisiana Department of Wildlife and Fisheries · USUnited States Fish and Wildlife Service · USUniversity of Maryland, College Park · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Avian influenza (AI) affects wild aquatic birds and poses hazards to human health, food security, and wildlife conservation globally. Accordingly, there is a recognized need for new methods and tools to help quantify the dynamic interaction between wild bird hosts and commercial poultry. Using satellite-marked waterfowl, we applied Bayesian joint hierarchical modeling to concurrently model species distributions, residency times, migration timing, and disease occurrence probability under an integrated animal movement and disease distribution modeling framework. Our results indicate that migratory waterfowl are positively related to AI occurrence over North America such that as waterfowl occurrence probability or residence time increase at a given location, so too does the chance of a commercial poultry AI outbreak. Analyses also suggest that AI occurrence probability is greatest during our observed waterfowl northward migration, and less during the southward migration. Methodologically, we found that when modeling disparate facets of disease systems at the wildlife-agriculture interface, it is essential that multiscale spatial patterns be addressed to avoid mistakenly inferring a disease process or disease-environment relationship from a pattern evaluated at the improper spatial scale. The study offers important insights into migratory waterfowl ecology and AI disease dynamics that aid in better preparing for future outbreaks.

Indexed as

AnimalsAnimals, WildBayes TheoremChickensDisease OutbreaksDucksInfluenza A virusInfluenza in BirdsNorth AmericaPoultry

Identifiers

PMID32054908
PMCPMC7018751
OpenAlexW3005714497

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.