Evidence map›Paper›PMID 26486591›Full record

ArticleScientific reports2015

The role of influenza in the epidemiology of pneumonia.

Sourya Shrestha, Betsy Foxman, Joshua Berus, Willem G van Panhuis, Claudia Steiner, Cécile Viboud, Pejman Rohani

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 7% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

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  18. Quantifying the consequences of measles-induced immune modulation for whooping cough epidemiology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
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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 at 6 institutions in 1 country.

Sourya ShresthaDepartment of Ecology &Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
Betsy FoxmanDepartment of Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA.
Joshua BerusUndergraduate Research Opportunity Program, University of Michigan, Ann Arbor, MI 48109, USA.
Willem G van PanhuisDepartment of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh PA 15261, USA.
Claudia SteinerHealthcare Cost and Utilization Project, Center for Delivery, Organization and Markets, Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, Rockville, MD 20850, USA.
Cécile ViboudDivision of International Epidemiology and Population Studies, National Institutes of Health, Bethesda, MD 20892, USA.
Pejman RohaniOdum School of Ecology, University of Georgia, Athens, GA 30602, USA.
University of Michigan–Ann Arbor · USAgency for Healthcare Research and Quality · USJohns Hopkins University · USNational Institutes of Health · USUniversity of Georgia · USUniversity of Pittsburgh · US

Funding

Training, Outreach & Diversity ComponentU54GM088491 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LAKOSKI, JOAN M · 2009 to 2018
$16.7M
Understanding Transmission with Integrated Genetic and Epidemiologic InferenceU54GM111274 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI VESPIGNANI, ALESSANDRO · 2014 to 2018
$12.5M
NIGMS NIH HHS U54 GM088491NIGMS NIH HHS U54 GM111274NIGMS NIH HHS U54-GM111274
6 · The paper itself

Abstract

Interactions arising from sequential viral and bacterial infections play important roles in the epidemiological outcome of many respiratory pathogens. Influenza virus has been implicated in the pathogenesis of several respiratory bacterial pathogens commonly associated with pneumonia. Though clinical evidence supporting this interaction is unambiguous, its population-level effects-magnitude, epidemiological impact and variation during pandemic and seasonal outbreaks-remain unclear. To address these unknowns, we used longitudinal influenza and pneumonia incidence data, at different spatial resolutions and across different epidemiological periods, to infer the nature, timing and the intensity of influenza-pneumonia interaction. We used a mechanistic transmission model within a likelihood-based inference framework to carry out formal hypothesis testing. Irrespective of the source of data examined, we found that influenza infection increases the risk of pneumonia by ~100-fold. We found no support for enhanced transmission or severity impact of the interaction. For model-validation, we challenged our fitted model to make out-of-sample pneumonia predictions during pandemic and non-pandemic periods. The consistency in our inference tests carried out on several distinct datasets, and the predictive skill of our model increase confidence in our overall conclusion that influenza infection substantially enhances the risk of pneumonia, though only for a short period.

Indexed as

HumansInfluenza, HumanLikelihood FunctionsOrthomyxoviridaePneumonia

Identifiers

PMID26486591
PMCPMC4614252
OpenAlexW2414392816

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.