ArticleFrontiers in public health2020
A Synergetic R-Shiny Portal for Modeling and Tracking of COVID-19 Data.
Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed.
- spconfShiny: An R Shiny application for calculating the spatial scale of smoothing splines for point data.PloS one · 2024Article
- Forecasting local hospital bed demand for COVID-19 using on-request simulations.Scientific reports · 2023Article
- Characteristics and specifications of dashboards developed for the COVID-19 pandemic: a scoping review.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2023Review
- Spatiotemporal analysis of the morbidity of global Omicron from November 2021 to February 2022.Journal of medical virology · 2022Article
- PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain.International journal of environmental research and public health · 2022Article
- A Web Application for Biomedical Text Mining of Scientific Literature Associated with Coronavirus-Related Syndromes: Coronavirus Finder.Diagnostics (Basel, Switzerland) · 2022Article
- A Web-Based Application to Monitor and Inform about the COVID-19 Outbreak in Italy: The {COVID-19ita} Initiative.Healthcare (Basel, Switzerland) · 2022Article
- Setting Requirements for a Dashboard to Inform Portuguese Decision-Makers About Environment Health in an Urban Setting.Frontiers in public health · 2022Article
- Applications, features and key indicators for the development of Covid-19 dashboards: A systematic review study.Informatics in medicine unlocked · 2022Article
- CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database.JAMIA open · 2021Article
- Factor analysis approach to classify COVID-19 datasets in several regions.Results in physics · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this paper is to introduce a useful online interactive dashboard (https://mahdisalehi.shinyapps.io/Covid19Dashboard/) that visualize and follow confirmed cases of COVID-19 in real-time. The dashboard was made publicly available on 6 April 2020 to illustrate the counts of confirmed cases, deaths, and recoveries of COVID-19 at the level of country or continent. This dashboard is intended as a user-friendly dashboard for researchers as well as the general public to track the COVID-19 pandemic, and is generated from trusted data sources and built in open-source R software (Shiny in particular); ensuring a high sense of transparency and reproducibility. The R Shiny framework serves as a platform for visualization and analysis of the data, as well as an advance to capitalize on existing data curation to support and enable open science. Coded analysis here includes logistic and Gompertz growth models, as two mathematical tools for predicting the future of the COVID-19 pandemic, as well as the Moran's index metric, which gives a spatial perspective via heat maps that may assist in the identification of latent responses and behavioral patterns. This analysis provides real-time statistical application aiming to make sense to academic- and public consumers of the large amount of data that is being accumulated due to the COVID-19 pandemic.
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Registered trials
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.