Evidence map›Paper›PMID 23199400›Full record

ReviewExpert review of anti-infective therapy2012

Prevention of influenza in healthy children.

Bruce Y Lee, Mirat Shah

Abstract readReview
In one paragraph

Review in Expert review of anti-infective therapy, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
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

2 authors.

Bruce Y LeePublic Health Computational and Operations Research, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, PA, USA. byl1@pitt.edu
Mirat Shah

Funding

Training, Outreach & Diversity ComponentU54GM088491 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LAKOSKI, JOAN M · 2009 to 2018
$16.7M
Core_plus Option_A_C_Influenza Surveillance and Vaccine Effectiveness in a LargeU01IP000467 · IP · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ZIMMERMAN, RICHARD K · 2011 to 2015
$5.9M
NCIRD CDC HHS U01 IP000467NIGMS NIH HHS 5U54GM088491-02NIGMS NIH HHS U54 GM088491
6 · The paper itself

Abstract

Healthy children are high transmitters of influenza and can experience poor influenza outcomes. Many questions remain about the efficacy and impect of preventive measures because most existing studies report imprecise proxies of influenza incidence, do not follow subjects throughout the entire influenza season and across multiple influenza seasons, or do not control for important factors such as timing of implementation and social contact patterns. Modeling and simulation are key methodologies to answer questions regarding influenza prevention. While vaccination may be the most efficacious existing intervention, variations in circulating strains and children's immune systems keep current vaccines from being fully protective, necessitating further clinical and economic studies and technology improvements. Hand hygiene appears to be an important adjunct but improving compliance, standardizing regimens and quantifying its impact remain challenging. Future studies should help better define the specific indications and circumstances for antiviral use and the role of nutritional supplements and nonpharmaceutical interventions.

Indexed as

AdolescentAntiviral AgentsChildChild, PreschoolDietary SupplementsHumansInfantInfluenza, HumanInfluenza VaccinesQuarantineAntiviral AgentsInfluenza Vaccines

Identifiers

PMID23199400
PMCPMC3763239

What OpenQuestion holds

Textmetadata
LicenceTDM
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.