Evidence map›Paper›PMID 31632600›Full record

ArticleOnline journal of public health informatics2019

The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of influenza.

Nicholas E Millett, John M Aronis, Michael M Wagner, Fuchiang Tsui, Ye Ye, Jeffrey P Ferraro, Peter J Haug, Per H Gesteland, Gregory F Cooper

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Online journal of public health informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 85% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 3 institutions in 1 country.

Nicholas E MillettReal-time Outbreak and Disease Surveillance (RODS) Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
John M AronisReal-time Outbreak and Disease Surveillance (RODS) Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
Michael M WagnerReal-time Outbreak and Disease Surveillance (RODS) Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
Fuchiang TsuiReal-time Outbreak and Disease Surveillance (RODS) Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
Ye YeReal-time Outbreak and Disease Surveillance (RODS) Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
Jeffrey P FerraroDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
Peter J HaugDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
Per H GestelandDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
Gregory F CooperReal-time Outbreak and Disease Surveillance (RODS) Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
University of Pittsburgh · USUniversity of Utah · USChildren's Hospital of Philadelphia · US

Funding

The internship in Biomedical Research, Informatics, and Computer Science (iBRIC): Biomedical Informatics and Data Science research experiences for students from Minority Serving InstitutionsT15LM007059 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRY S HOCHHEISER · 1987 to 2026
$23.9M
MIDAS Informatics Services Group (ISG)U24GM110707 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ESPINO, JESSI U, WAGNER, MICHAEL MATTHEW · 2014 to 2018
$11.6M
Probabilistic Disease SurveillanceR01LM011370 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WAGNER, MICHAEL MATTHEW · 2013 to 2015
$1.7M
NIGMS NIH HHS U24 GM110707NLM NIH HHS R01 LM011370NLM NIH HHS T15 LM007059
6 · The paper itself

Abstract

The prediction and characterization of outbreaks of infectious diseases such as influenza remains an open and important problem. This paper describes a framework for detecting and characterizing outbreaks of influenza and the results of testing it on data from ten outbreaks collected from two locations over five years. We model outbreaks with compartment models and explicitly model non-influenza influenza-like illnesses.

Identifiers

PMID31632600
PMCPMC6788888
OpenAlexW2975590600

What OpenQuestion holds

Textmetadata
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.