Evidence map›Paper›PMID 33274066›Full record

SynthesisJournal of global health2020

Variability in published rates of influenza-associated hospitalizations: A systematic review, 2007-2018.

Katherine M Roguski, Melissa A Rolfes, Jeremy S Reich, Zachary Owens, Neha Patel, Julia Fitzner, Vanessa Cozza, Kathryn E Lafond, Eduardo Azziz-Baumgartner, A Danielle Iuliano

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

10 authors.

Katherine M RoguskiUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
Melissa A RolfesUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
Jeremy S ReichUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
Zachary OwensEmory University, Rollins School of Public Health, Department of Epidemiology, Atlanta, Georgia, USA.
Neha PatelUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
Julia FitznerWorld Health Organization, Global Influenza Programme, Geneva, Switzerland.
Vanessa CozzaWorld Health Organization, Global Influenza Programme, Geneva, Switzerland.
Kathryn E LafondUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
Eduardo Azziz-BaumgartnerUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
A Danielle IulianoUS Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundInfluenza burden estimates help provide evidence to support influenza prevention and control programs at local and international levels.

methodsThrough a systematic review, we aimed to identify all published articles estimating rates of influenza-associated hospitalizations, describe methods and data sources used, and identify regions of the world where estimates are still lacking. We evaluated study heterogeneity to determine if we could pool published rates to generate global estimates of influenza-associated hospitalization.

resultsWe identified 98 published articles estimating influenza-associated hospitalization rates from 2007-2018. Most articles (65%) identified were from high-income countries, with 34 of those (53%) presenting estimates from the United States. While we identified fewer publications (18%) from low- and lower-middle-income countries, 50% of those were published from 2015-2018, suggesting an increase in publications from lower-income countries in recent years. Eighty percent (n = 78) used a multiplier approach. Regression modelling techniques were only used with data from upper-middle or high-income countries where hospital administrative data was available. We identified variability in the methods, case definitions, and data sources used, including 91 different age groups and 11 different categories of case definitions. Due to the high observed heterogeneity across articles (

conclusionsThe variety of methods, data sources, and case definitions adapted locally suggests that the current literature cannot be synthesized to generate global estimates of influenza-associated hospitalization burden.

Indexed as

BibliometricsInfluenza, HumanHospitalizationHumansRegression Analysis

Identifiers

PMID33274066
PMCPMC7699004

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.