Evidence map›Paper›PMID 36298475›Full record

ArticleVaccines2022

Influenza Vaccine Uptake in the United States before and during the COVID-19 Pandemic.

Ian McGovern, Alina Bogdanov, Katherine Cappell, Sam Whipple, Mendel Haag

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

23 citing papers in PubMed, 30 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

5 authors at 1 institution in 1 country.

Ian McGovernSeqirus Inc., Cambridge, MA 02139, USA.ORCID 0000-0002-0282-7728
Alina BogdanovVeradigm, San Francisco, CA 94103, USA.
Katherine CappellVeradigm, San Francisco, CA 94103, USA.
Sam WhippleVeradigm, San Francisco, CA 94103, USA.
Mendel HaagSeqirus NL BV, 1105 Amsterdam, The Netherlands.
Seqirus (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic, along with disruptions to routine medical care, brought renewed urgency to public health messaging about the importance of influenza vaccination. This retrospective cohort study used a database of linked claims and electronic medical record data to evaluate clinical and demographic characteristics and influenza vaccination history associated with changes in influenza vaccine uptake following the start of the COVID-19 pandemic. Influenza vaccine uptake was examined in six seasons (2015−2016 through 2020−2021). Individuals were grouped by vaccination history in the five seasons before 2020−2021. Characteristics of 2020−2021 vaccinated vs. unvaccinated individuals were compared, stratified by vaccination history. Overall influenza vaccination uptake was highest in 2020−2021 (35.4%), following a trend of increasing uptake since 2016−2017 (31.4%). Uptake in 2020−2021 was observed in all age groups except ≥65 years, and the increase was particularly notable in individuals <18 years. In the previous five seasons, individuals ≤17 and >65 years, White, and Asian individuals were most likely, while 18-to-49-year-olds and those with fewer comorbidities were least likely, to be consistently vaccinated. Influenza vaccination status in 2020−2021 aligned with vaccination history; few differences in patient characteristics (age, comorbidities, state of residence) were observed when stratified by vaccination history.

Indexed as

administrative claimsCOVID-19electronic medical recordsinfluenza seasonsinfluenza vaccinevaccination coveragevaccine uptake

Identifiers

PMID36298475
PMCPMC9612058
OpenAlexW4298003299

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.