Evidence map›Paper›PMID 32607525›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Influenza Vaccination and COVID19 Mortality in the USA.

Claudio Zanettini, Mohamed Omar, Wikum Dinalankara, Eddie Luidy Imada, Elizabeth Colantuoni, Giovanni Parmigiani, Luigi Marchionni

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Systems Thinking About SARS-CoV-2.Frontiers in public health · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Claudio ZanettiniDepartment of Oncology, Johns Hopkins University, Baltimore, MD, USA.
Mohamed OmarDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
Wikum DinalankaraDepartment of Oncology, Johns Hopkins University, Baltimore, MD, USA.
Eddie Luidy ImadaDepartment of Oncology, Johns Hopkins University, Baltimore, MD, USA.
Elizabeth ColantuoniDepartment of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
Giovanni ParmigianiDepartment of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
Luigi MarchionniDepartment of Oncology, Johns Hopkins University, Baltimore, MD, USA.

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rosalie Wollett · 1985 to 2026
$208.6M
NCI NIH HHS P30 CA006973
6 · The paper itself

Abstract

COVID-19 mortality rate is higher in the elderly and in those with preexisting chronic medical conditions. The elderly also suffer from increased morbidity and mortality from seasonal influenza infection, and thus annual influenza vaccination is recommended for them. In this study, we explore a possible area-level association between influenza vaccination coverage in people aged 65 years and older and the number of deaths from COVID-19. To this end, we used COVID-19 data until June 10, 2020 together with population health data for the United States at the county level. We fit quasi-Poisson regression models using influenza vaccination coverage in the elderly population as the independent variable and the number of deaths from COVID-19 as the outcome variable. We adjusted for a wide array of potential confounding variables using both county-level generalized propensity scores for influenza vaccination rates, as well as direct adjustment. Our results suggest that influenza vaccination coverage in the elderly population is negatively associated with mortality from COVID-19. This finding is robust to using different analysis periods, different thresholds for inclusion of counties, and a variety of methodologies for confounding adjustment. In conclusion, our results suggest a potential protective effect of the influenza vaccine on COVID-19 mortality in the elderly population. The significant public health implications of this possibility point to an urgent need for studying the relationship between influenza vaccination and COVID-19 mortality at the individual level, to investigate both the epidemiology and any underlying biological mechanism.

Identifiers

PMID32607525
PMCPMC7325191

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.