Evidence map›Paper›PMID 36877539›Full record

ArticleJournal of medical Internet research2023

A Platform for Data-Centric, Continuous Epidemiological Analyses (EpiGraphHub): Descriptive Analysis.

Flávio Coelho, Daniel Cardoso Portela Câmara, Eduardo Correa Araújo, Lucas Monteiro Bianchi, Ivan Ogasawara, Jyoti Dalal, Ananthu James, Jessica L Abbate, Aziza Merzouki, Izabel Cristina Dos Reis and 2 more

Full text read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

12 authors.

Flávio CoelhoSchool of Applied Mathematics, Fundação Getulio Vargas, Rio de Janeiro, Brazil.ORCID 0000-0003-3868-4391
Daniel Cardoso Portela Câmara *The Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-5439-4477
Eduardo Correa AraújoThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-4032-6123
Lucas Monteiro BianchiThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0001-7160-1143
Ivan OgasawaraThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0001-5049-4289
Jyoti DalalThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-5817-026X
Ananthu JamesThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-2562-347X
Jessica L AbbateThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0003-2485-3334
Aziza MerzoukiThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-6418-2945
Izabel Cristina Dos ReisThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-1961-6556
Kene David NwosuThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0002-3245-4109
Olivia KeiserThe Global Research and Analysis for Public Health Network, Geneva, Switzerland.ORCID 0000-0001-8191-2789

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGuaranteeing durability, provenance, accessibility, and trust in open data sets can be challenging for researchers and organizations that rely on public repositories of data critical for epidemiology and other health analytics. The required data repositories are often difficult to locate and may require conversion to a standard data format. Data-hosting websites may also change or become unavailable without warning. A single change to the rules in one repository can hinder updating a public dashboard reliant on data pulled from external sources. These concerns are particularly challenging at the international level, because policies on systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs.

objectiveIn this paper, we introduce a comprehensive public health data platform, EpiGraphHub, that aims to provide a single interoperable repository for open health and related data.

methodsThe platform, curated by the international research community, allows secure local integration of sensitive data while facilitating the development of data-driven applications and reports for decision-makers. Its main components include centrally managed databases with fine-grained access control to data, fully automated and documented data collection and transformation, and a powerful web-based data exploration and visualization tool.

resultsEpiGraphHub is already being used for hosting a growing collection of open data sets and for automating epidemiological analyses based on them. The project has also released an open-source software library with the analytical methods used in the platform.

conclusionsThe platform is fully open source and open to external users. It is in active development with the goal of maximizing its value for large-scale public health studies.

Indexed as

Data AnalysisPublic HealthDatabases, FactualData CollectionFederal GovernmentHumansaccessibilityapplicationdatadata analysisdata sciencedata setdecisiondecision-makingdisease surveillancedurabilityepidemiologyplatformpublicpublic health

Identifiers

PMID36877539
PMCPMC10028505

What OpenQuestion holds

Textfull text, public
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.