A Platform for Data-centric, Continuous Epidemiological Analyses
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Guaranteeing durability, provenance, accessibility, and trust in open datasets can be challenging for researchers and organizations that rely on public repositories of data critical to epidemiology and other health analytics. Not only are the required repositories sometimes difficult to locate, and nearly always require conversion into a compatible format, they may move or change unpredictably. Any single change of the rules in one repository can hinder updating of a public dashboard reliant on pulling data from external sources. These concerns are particularly challenging at the international level, because systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs. In this paper, we introduce a comprehensive public health data platform, the EpiGraphHub, that aims to provide a single interoperable repository for open health and related data, curated by the international research community, which allows secure local integration of sensitive databases whilst facilitating the development of data-driven applications and reports for decision-makers. The platform development is co-funded by the World Health Organization and is fully open-source to maximize its value for large-scale public health studies.
Article activity feed
-
SciScore for 10.1101/2022.04.19.22274026: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources To maximize code re-usability and value for the open source community, all the tools for data collection, transformation and analysis are developed as EpiGraphHub software libraries available both in Python and the R languages. Pythonsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques …SciScore for 10.1101/2022.04.19.22274026: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources To maximize code re-usability and value for the open source community, all the tools for data collection, transformation and analysis are developed as EpiGraphHub software libraries available both in Python and the R languages. Pythonsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-
-