Evidence map›Paper›PMID 26958299›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2015

Analyses of Merging Clinical and Viral Genetic Data for Influenza Surveillance.

Daniel Magee, Rachel Beard, Matthew Scotch

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Daniel MageeArizona State University, Tempe, AZ, USA.
Rachel BeardArizona State University, Tempe, AZ, USA.
Matthew ScotchArizona State University, Tempe, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The annual influenza vaccine is one of the most common public health interventions and is universally recommended for all individuals older than six months. Vaccine composition depends on viruses circulating over the past flu season and are estimated to be the most prevalent and representative strains in the current season. Here, we use clinical data outfitted with viral genetics to characterize confirmed influenza cases from the past two flu seasons and genetically compare them to the strains that they were vaccinated against that year. We show that case similarities to vaccine strains differ by geographic region and that the vaccines appear to have different levels of effectiveness by region. This study demonstrates the value of merging viral genetics with clinical data. Further research is needed to formally evaluate whether this improves biosurveillance efforts and enhances efficacy of influenza vaccines.

Indexed as

Influenza VaccinesPublic HealthGenes, ViralHumansInfluenza, HumanSeasonsInfluenza Vaccines

Identifiers

PMID26958299
PMCPMC4765576

What OpenQuestion holds

Textmetadata
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.