Evidence map›Paper›PMID 21388566›Full record

ReviewBMC public health2011

Department of Defense influenza and other respiratory disease surveillance during the 2009 pandemic.

Ronald L Burke, Kelly G Vest, Angelia A Eick, Jose L Sanchez, Matthew C Johns, Julie A Pavlin, Richard G Jarman, Jerry L Mothershead, Miguel Quintana, Thomas Palys and 72 more

Open access · goldAbstract readReview
In one paragraph

Review in BMC public health, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

11 citing papers in PubMed, 81 citations in OpenAlex.

  1. Article
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  4. Review
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  9. Review
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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

82 authors at 12 institutions in 5 countries.

Ronald L BurkeArmed Forces Health Surveillance Center, 503 Robert Grant Avenue, Silver Spring, MD 20910, USA. Ronald.L.Burke@us.army.mil
Kelly G Vest
Angelia A Eick
Jose L Sanchez
Matthew C Johns
Julie A Pavlin
Richard G Jarman
Jerry L Mothershead
Miguel Quintana
Thomas Palys
Michael J Cooper
Jian Guan
David Schnabel
John Waitumbi
Alisa Wilma
Candelaria Daniels
Matthew L Brown
Steven Tobias
Matthew R Kasper
Maya Williams
Jeffrey A Tjaden
Buhari Oyofo
Timothy Styles
Patrick J Blair
Anthony Hawksworth
Joel M Montgomery
Hugo Razuri
Alberto Laguna-Torres
Randal J Schoepp
David A Norwood
Victor H Macintosh
Thomas Gibbons
Gregory C Gray
David L Blazes
Kevin L Russell
AFHSC-GEIS Influenza Surveillance Writing Group
Jennifer Rubenstein
Kyle Hathaway
Robert Gibbons
In-Kyu Yoon
David Saunders
Jariyanart Gaywee
Mikal Stoner
Ans Timmermans
Sanjaya K Shrestha
John Mark S Velasco
Maria T Alera
Darunee Tannitisupawong
Khin Saw Myint
Sathit Pichyangkul
Ben Woods
Kurt H Jerke
Michael G Koenig
Denis K Byarugaba
Fred Wabwire Mangen
Berhane Assefa
Maya Williams
Gary Brice
Moustafa Mansour
Guillermo Pimentel
Peter Sebeny
Maha Talaat
Tamer Saeed
Ben Espinosa
Dennis Faix
Ryan Maves
Tadeusz Kochel
James Smith
Alicia Guerrero
Gen Maupin
Paul Sjoberg
Mark Duffy
Jason Garner
Linda Canas
Elizabeth Macias
Robert A Kuschner
Dennis Shanks
Sheri Lewis
Gosia Nowak
Lucy M Ndip
Nathan Wolfe
Karen Saylors
Armed Forces Health Surveillance Center · USNaval Medical Research Unit Six · PEArmed Forces Research Institute of Medical Science · THNaval Health Research Center · USUnited States Air Force · USUnited States Army Medical Research Institute of Infectious Diseases · USUnited States Department of Defense · USUnited States Naval Medical Research Unit III · EGLandstuhl Regional Medical Center · DEUniformed Services University of the Health Sciences · USUnited States NavyUniversity of Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Armed Forces Health Surveillance Center's Division of Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) supports and oversees surveillance for emerging infectious diseases, including respiratory diseases, of importance to the U.S. Department of Defense (DoD). AFHSC-GEIS accomplishes this mission by providing funding and oversight to a global network of partners for respiratory disease surveillance. This report details the system's surveillance activities during 2009, with a focus on efforts in responding to the novel H1N1 Influenza A (A/H1N1) pandemic and contributions to global public health. Active surveillance networks established by AFHSC-GEIS partners resulted in the initial detection of novel A/H1N1 influenza in the U.S. and several other countries, and viruses isolated from these activities were used as seed strains for the 2009 pandemic influenza vaccine. Partners also provided diagnostic laboratory training and capacity building to host nations to assist with the novel A/H1N1 pandemic global response, adapted a Food and Drug Administration-approved assay for use on a ruggedized polymerase chain reaction platform for diagnosing novel A/H1N1 in remote settings, and provided estimates of seasonal vaccine effectiveness against novel A/H1N1 illness. Regular reporting of the system's worldwide surveillance findings to the global public health community enabled leaders to make informed decisions on disease mitigation measures and controls for the 2009 A/H1N1 influenza pandemic. AFHSC-GEIS's support of a global network contributes to DoD's force health protection, while supporting global public health.

Indexed as

Global HealthInfluenza A Virus, H1N1 SubtypeSentinel SurveillanceHumansInfluenza, HumanMilitary MedicinePandemicsRespiratory Tract DiseasesUnited StatesUnited States Department of Defense

Identifiers

PMID21388566
PMCPMC3092416
OpenAlexW2024648570

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.