Evidence map›Paper›PMID 25461850›Full record

ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2015

Temporal dynamics, diversity, and interplay in three components of the virodiversity of a Mallard population: influenza A virus, avian paramyxovirus and avian coronavirus.

Michelle Wille, Alexis Avril, Conny Tolf, Anna Schager, Sara Larsson, Olivia Borg, Björn Olsen, Jonas Waldenström

Abstract read
In one paragraph

Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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

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  16. Continental-scale dynamics of avian influenza in U.S. waterfowl are driven by demography, migration, and temperature.Ecological applications : a publication of the Ecological Society of America · 2021
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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.

Michelle WilleCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden.
Alexis AvrilCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden; CIRAD, Campus international de Baillarguet, 34398 Montpellier, France.
Conny TolfCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden.
Anna SchagerCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden.
Sara LarssonCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden.
Olivia BorgCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden.
Björn OlsenSection of Infectious Diseases, Department of Medical Sciences, Uppsala University, SE-751 85 Uppsala, Sweden; Zoonosis Science Centre, Department of Medical Biochemistry and Microbiology, Uppsala University, SE-751 85 Uppsala, Sweden.
Jonas WaldenströmCentre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, SE-391 82 Kalmar, Sweden. Electronic address: jonas.waldenstrom@lnu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple infections, or simultaneous infection of a host with multiple parasites, are the rule rather than the exception. Interactions between co-occurring pathogens in a population may be mutualistic, competitive or facilitative. For some pathogen combinations, these interrelated effects will have epidemiological consequences; however this is as yet poorly incorporated into practical disease ecology. For example, screening of Mallards for influenza A viruses (IAV) have repeatedly revealed high prevalence and large subtype diversity in the Northern Hemisphere. Other studies have identified avian paramyxovirus type 1 (APMV-1) and coronaviruses (CoVs) in Mallards, but without making inferences on the larger viral assemblage. In this study we followed 144 wild Mallards across an autumn season in a natural stopover site and constructed infection histories of IAV, APMV-1 and CoV. There was a high prevalence of IAV, comprising of 27 subtype combinations, while APMV-1 had a comparatively low prevalence (with a peak of 2%) and limited strain variation, similar to previous findings. Avian CoVs were common, with prevalence up to 12%, and sequence analysis identified different putative genetic lineages. An investigation of the dynamics of co-infections revealed a synergistic effect between CoV and IAV, whereby CoV prevalence was higher given that the birds were co-infected with IAV. There were no interactive effects between IAV and APMV-1. Disease dynamics are the result of an interplay between parasites, host immune responses, and resources; and is imperative that we begin to include all factors to better understand infectious disease risk.

Indexed as

DucksAnimalsAvulavirusBird DiseasesCoinfectionCoronavirusFemaleGenetic VariationInfluenza A virusMalePhylogenyPrevalenceRNA, ViralSequence Analysis, RNARNA, ViralAvian paramyxovirusCo-infectionCoronavirusDisease dynamicsInfluenza A virusNewcastle disease virus

Identifiers

PMID25461850
PMCPMC7106038

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Registered trials

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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.