Evidence map›Paper›PMID 31702114›Full record

ArticleInfluenza and other respiratory viruses2020

State-level estimates of excess hospitalizations and deaths associated with influenza.

Christopher A Czaja, Lisa Miller, Kathryn Colborn, Myles G Cockburn, Nisha Alden, Rachel K Herlihy, Eric A F Simões

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Article in Influenza and other respiratory viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
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10citing papers in PubMed, 1 pooled it
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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

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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

10 citing papers in PubMed, 1 synthesis or guideline 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

7 authors.

Christopher A CzajaColorado Department of Public Health and Environment, Denver, CO, USA.ORCID 0000-0002-1742-514X
Lisa MillerColorado School of Public Health, Aurora, CO, USA.
Kathryn ColbornColorado School of Public Health, Aurora, CO, USA.
Myles G CockburnColorado School of Public Health, Aurora, CO, USA.
Nisha AldenColorado Department of Public Health and Environment, Denver, CO, USA.
Rachel K HerlihyColorado Department of Public Health and Environment, Denver, CO, USA.
Eric A F SimõesColorado School of Public Health, Aurora, CO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNational estimates of influenza burden may not reflect state-level influenza activity, and local surveillance may not capture the full burden of influenza.

methodsTo provide state-level information about influenza burden, we estimated excess pneumonia and influenza (P&I) and respiratory and circulatory (R&C) hospitalizations and deaths in Colorado from local hospital discharge records, death certificates, and influenza virus surveillance using negative binomial models.

resultsFrom July 2007 to June 2016, influenza was associated with an excess of 17 911 P&I hospitalizations (95%CI: 15 227, 20 354), 30 811 R&C hospitalizations (95%CI: 24 344, 37 176), 1,064 P&I deaths (95%CI: 757, 1298), and 3828 R&C deaths (95%CI: 2060, 5433). There was a large burden of influenza A(H1N1) among persons aged 0-64 years, with high median seasonal rates of excess hospitalization among persons aged 0-4 years. Persons aged ≥65 years experienced the largest numbers and highest median seasonal rates of excess hospitalization and death associated with influenza A (H3N2). The burden of influenza B was generally lower, with elevated median seasonal rates of excess hospitalization among persons aged 0-4 years and ≥65 years.

conclusionsThese findings complement existing influenza surveillance. Periodic state-level estimates of influenza disease burden may be useful for setting state public health priorities and planning prevention and control initiatives.

Indexed as

AdolescentAdultAgedAged, 80 and overChildChild, PreschoolColoradoFemaleHospitalizationHumansInfantInfant, NewbornInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza, HumanMaledeathhospitalizationhumaninfluenzapublic health

Identifiers

PMID31702114
PMCPMC7040963

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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.